Overview

Brought to you by YData

Dataset statistics

Number of variables129
Number of observations26208
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory27.0 MiB
Average record size in memory1.1 KiB

Variable types

DateTime1
Categorical128

Dataset

DescriptionSix-Month Monitoring Dataset from a 10-Turbine Onshore Wind Farm in Greece.
URLhttps://doi.org/10.5281/zenodo.14546479

Alerts

Gear Oil Temp. Avg. [°C] has constant value "0" Constant
Gear Bearing Temp. Avg. [°C] has constant value "0" Constant
Gear Oil TemperatureLevel2_3 Avg. [°C] has constant value "0" Constant
Ambient WindSpeed Estimated Avg. [m/s] has constant value "0" Constant
Grid Production PossibleInductive Avg. [var] has constant value "0" Constant
Grid Production PossibleInductive Max. [var] has constant value "0" Constant
Grid Production PossibleInductive Min. [var] has constant value "0" Constant
Grid Production PossibleInductive StdDev [var] has constant value "0" Constant
Grid Production PossibleCapacitive Avg. [var] has constant value "0" Constant
Grid Production PossibleCapacitive Max. [var] has constant value "0" Constant
Grid Production PossibleCapacitive Min. [var] has constant value "0" Constant
Grid Production PossibleCapacitive StdDev [var] has constant value "0" Constant
Reactive power set point [var] has constant value "0" Constant
Spinner Temp. SlipRing Avg. [°C] has constant value "0" Constant
HourCounters Average Total Avg. [h] has constant value "0" Constant
Total hour counter [h] has constant value "0" Constant
Grid on hours [h] has constant value "0" Constant
Grid ok hours [h] has constant value "0" Constant
Turbine ok hours [h] has constant value "0" Constant
Run hours [h] has constant value "0" Constant
Generator 1 hours [h] has constant value "0" Constant
Generator 2 hours [h] has constant value "0" Constant
Yaw hours [h] has constant value "0" Constant
Service hours [h] has constant value "0" Constant
Ambient ok hours [h] has constant value "0" Constant
Wind ok hours [h] has constant value "0" Constant
Active power generator 0, Total accumulated [W] has constant value "0" Constant
Active power generator 1, Total accumulated [W] has constant value "0" Constant
Reactive power generator 1, Total accumulated [var] has constant value "0" Constant
Reactive power generator 2, Total accumulated [var] has constant value "0" Constant
Active power limit source is highly overall correlated with Power factor set point and 1 other fieldsHigh correlation
Blades PitchAngle Min. [°] is highly overall correlated with Blades PitchAngle StdDev [°] and 2 other fieldsHigh correlation
Blades PitchAngle StdDev [°] is highly overall correlated with Blades PitchAngle Min. [°]High correlation
Generator Phase1 Temp. Avg. [°C] is highly overall correlated with Generator Phase2 Temp. Avg. [°C] and 1 other fieldsHigh correlation
Generator Phase2 Temp. Avg. [°C] is highly overall correlated with Generator Phase1 Temp. Avg. [°C]High correlation
Generator Phase3 Temp. Avg. [°C] is highly overall correlated with Generator Phase1 Temp. Avg. [°C]High correlation
Generator RPM Avg. [RPM] is highly overall correlated with Rotor RPM Avg. [RPM]High correlation
Generator RPM Max. [RPM] is highly overall correlated with Rotor RPM Max. [RPM]High correlation
Generator RPM Min. [RPM] is highly overall correlated with Rotor RPM Min. [RPM]High correlation
Generator RPM StdDev [RPM] is highly overall correlated with Rotor RPM StdDev [RPM]High correlation
Grid Production CosPhi Avg. is highly overall correlated with Production LatestAverage Active Power Gen 0 Avg. [W]High correlation
Grid Production CurrentPhase1 Avg. [A] is highly overall correlated with Grid Production CurrentPhase2 Avg. [A] and 3 other fieldsHigh correlation
Grid Production CurrentPhase2 Avg. [A] is highly overall correlated with Grid Production CurrentPhase1 Avg. [A] and 4 other fieldsHigh correlation
Grid Production CurrentPhase3 Avg. [A] is highly overall correlated with Grid Production CurrentPhase1 Avg. [A] and 4 other fieldsHigh correlation
Grid Production PossiblePower Avg. [W] is highly overall correlated with Grid Production CurrentPhase2 Avg. [A] and 3 other fieldsHigh correlation
Grid Production PossiblePower Max. [W] is highly overall correlated with Grid Production Power Max. [W]High correlation
Grid Production PossiblePower StdDev [W] is highly overall correlated with Grid Production Power StdDev [W]High correlation
Grid Production Power Avg. [W] is highly overall correlated with Grid Production CurrentPhase1 Avg. [A] and 4 other fieldsHigh correlation
Grid Production Power Max. [W] is highly overall correlated with Grid Production PossiblePower Max. [W]High correlation
Grid Production Power StdDev [W] is highly overall correlated with Grid Production PossiblePower StdDev [W]High correlation
Grid Production ReactivePower Avg. [W] is highly overall correlated with Blades PitchAngle Min. [°] and 6 other fieldsHigh correlation
Grid Production ReactivePower Max. [W] is highly overall correlated with Grid Production ReactivePower Avg. [W]High correlation
Grid Production ReactivePower StdDev [W] is highly overall correlated with Grid Production ReactivePower Avg. [W]High correlation
Grid Production VoltagePhase1 Avg. [V] is highly overall correlated with Grid Production VoltagePhase2 Avg. [V] and 1 other fieldsHigh correlation
Grid Production VoltagePhase2 Avg. [V] is highly overall correlated with Grid Production VoltagePhase1 Avg. [V] and 1 other fieldsHigh correlation
Grid Production VoltagePhase3 Avg. [V] is highly overall correlated with Grid Production VoltagePhase1 Avg. [V] and 1 other fieldsHigh correlation
HourCounters Average AlarmActive Avg. [h] is highly overall correlated with HourCounters Average AmbientOk Avg. [h] and 1 other fieldsHigh correlation
HourCounters Average AmbientOk Avg. [h] is highly overall correlated with HourCounters Average AlarmActive Avg. [h] and 4 other fieldsHigh correlation
HourCounters Average Gen1 Avg. [h] is highly overall correlated with Production LatestAverage Active Power Gen 1 Avg. [W]High correlation
HourCounters Average Gen2 Avg. [h] is highly overall correlated with Blades PitchAngle Min. [°] and 3 other fieldsHigh correlation
HourCounters Average GridOk Avg. [h] is highly overall correlated with HourCounters Average AmbientOk Avg. [h] and 2 other fieldsHigh correlation
HourCounters Average GridOn Avg. [h] is highly overall correlated with HourCounters Average AmbientOk Avg. [h] and 2 other fieldsHigh correlation
HourCounters Average Run Avg. [h] is highly overall correlated with HourCounters Average AlarmActive Avg. [h] and 2 other fieldsHigh correlation
HourCounters Average TurbineOk Avg. [h] is highly overall correlated with HourCounters Average AmbientOk Avg. [h] and 3 other fieldsHigh correlation
Power factor set point is highly overall correlated with Active power limit source and 1 other fieldsHigh correlation
Power factor set point source is highly overall correlated with Active power limit source and 1 other fieldsHigh correlation
Production LatestAverage Active Power Gen 0 Avg. [W] is highly overall correlated with Grid Production CosPhi Avg. and 3 other fieldsHigh correlation
Production LatestAverage Active Power Gen 1 Avg. [W] is highly overall correlated with HourCounters Average Gen1 Avg. [h]High correlation
Production LatestAverage Reactive Power Gen 0 Avg. [var] is highly overall correlated with Grid Production ReactivePower Avg. [W] and 3 other fieldsHigh correlation
Production LatestAverage Reactive Power Gen 1 Avg. [var] is highly overall correlated with Production LatestAverage Total Reactive Power Avg. [var]High correlation
Production LatestAverage Total Active Power Avg. [W] is highly overall correlated with Grid Production CurrentPhase1 Avg. [A] and 4 other fieldsHigh correlation
Production LatestAverage Total Reactive Power Avg. [var] is highly overall correlated with Grid Production ReactivePower Avg. [W] and 2 other fieldsHigh correlation
Rotor RPM Avg. [RPM] is highly overall correlated with Generator RPM Avg. [RPM]High correlation
Rotor RPM Max. [RPM] is highly overall correlated with Generator RPM Max. [RPM]High correlation
Rotor RPM Min. [RPM] is highly overall correlated with Generator RPM Min. [RPM]High correlation
Rotor RPM StdDev [RPM] is highly overall correlated with Generator RPM StdDev [RPM]High correlation
Generator RPM Max. [RPM] is highly imbalanced (61.8%) Imbalance
Generator RPM Min. [RPM] is highly imbalanced (54.2%) Imbalance
Generator RPM Avg. [RPM] is highly imbalanced (57.9%) Imbalance
Generator RPM StdDev [RPM] is highly imbalanced (57.7%) Imbalance
Generator Bearing Temp. Avg. [°C] is highly imbalanced (77.1%) Imbalance
Generator Phase1 Temp. Avg. [°C] is highly imbalanced (76.3%) Imbalance
Generator Phase2 Temp. Avg. [°C] is highly imbalanced (78.1%) Imbalance
Generator Phase3 Temp. Avg. [°C] is highly imbalanced (79.3%) Imbalance
Generator SlipRing Temp. Avg. [°C] is highly imbalanced (56.3%) Imbalance
Generator Bearing2 Temp. Avg. [°C] is highly imbalanced (78.6%) Imbalance
Hydraulic Oil Temp. Avg. [°C] is highly imbalanced (82.7%) Imbalance
Gear Oil TemperatureBasis Avg. [°C] is highly imbalanced (64.9%) Imbalance
Gear Oil TemperatureLevel1 Avg. [°C] is highly imbalanced (70.8%) Imbalance
Gear Bearing TemperatureHSRotorEnd Avg. [°C] is highly imbalanced (77.9%) Imbalance
Gear Bearing TemperatureHSGeneratorEnd Avg. [°C] is highly imbalanced (75.2%) Imbalance
Gear Bearing TemperatureHSMiddle Avg. [°C] is highly imbalanced (71.5%) Imbalance
Gear Bearing TemperatureHollowShaftRotor Avg. [°C] is highly imbalanced (61.5%) Imbalance
Gear Bearing TemperatureHollowShaftGenerator Avg. [°C] is highly imbalanced (65.0%) Imbalance
Nacelle Temp. Avg. [°C] is highly imbalanced (56.6%) Imbalance
Rotor RPM Max. [RPM] is highly imbalanced (51.8%) Imbalance
Rotor RPM Avg. [RPM] is highly imbalanced (56.2%) Imbalance
Ambient WindSpeed Max. [m/s] is highly imbalanced (89.7%) Imbalance
Ambient WindSpeed Min. [m/s] is highly imbalanced (85.6%) Imbalance
Ambient WindSpeed Avg. [m/s] is highly imbalanced (91.7%) Imbalance
Ambient WindSpeed StdDev [m/s] is highly imbalanced (70.0%) Imbalance
Ambient WindDir Relative Avg. [°] is highly imbalanced (80.5%) Imbalance
Ambient WindDir Absolute Avg. [°] is highly imbalanced (84.1%) Imbalance
Ambient Temp. Avg. [°C] is highly imbalanced (50.9%) Imbalance
Grid InverterPhase1 Temp. Avg. [°C] is highly imbalanced (65.5%) Imbalance
Grid RotorInvPhase1 Temp. Avg. [°C] is highly imbalanced (59.8%) Imbalance
Grid RotorInvPhase2 Temp. Avg. [°C] is highly imbalanced (56.6%) Imbalance
Grid RotorInvPhase3 Temp. Avg. [°C] is highly imbalanced (57.8%) Imbalance
Grid Production Power Avg. [W] is highly imbalanced (75.1%) Imbalance
Grid Production CosPhi Avg. is highly imbalanced (68.0%) Imbalance
Grid Production Frequency Avg. [Hz] is highly imbalanced (95.7%) Imbalance
Grid Production VoltagePhase1 Avg. [V] is highly imbalanced (92.6%) Imbalance
Grid Production VoltagePhase2 Avg. [V] is highly imbalanced (92.0%) Imbalance
Grid Production VoltagePhase3 Avg. [V] is highly imbalanced (91.5%) Imbalance
Grid Production CurrentPhase1 Avg. [A] is highly imbalanced (74.4%) Imbalance
Grid Production CurrentPhase2 Avg. [A] is highly imbalanced (74.5%) Imbalance
Grid Production CurrentPhase3 Avg. [A] is highly imbalanced (75.6%) Imbalance
Grid Production Power Max. [W] is highly imbalanced (68.1%) Imbalance
Grid Production Power Min. [W] is highly imbalanced (66.4%) Imbalance
Grid Busbar Temp. Avg. [°C] is highly imbalanced (73.8%) Imbalance
Grid Production Power StdDev [W] is highly imbalanced (72.0%) Imbalance
Grid Production ReactivePower Avg. [W] is highly imbalanced (57.9%) Imbalance
Grid Production PossiblePower Avg. [W] is highly imbalanced (82.3%) Imbalance
Grid Production PossiblePower Max. [W] is highly imbalanced (78.3%) Imbalance
Grid Production PossiblePower Min. [W] is highly imbalanced (75.1%) Imbalance
Grid Production PossiblePower StdDev [W] is highly imbalanced (78.4%) Imbalance
Active power limit [W] is highly imbalanced (88.3%) Imbalance
Active power limit source is highly imbalanced (97.8%) Imbalance
Power factor set point is highly imbalanced (97.8%) Imbalance
Power factor set point source is highly imbalanced (97.8%) Imbalance
Controller Ground Temp. Avg. [°C] is highly imbalanced (86.2%) Imbalance
Controller Top Temp. Avg. [°C] is highly imbalanced (69.7%) Imbalance
Controller VCP Temp. Avg. [°C] is highly imbalanced (59.1%) Imbalance
Controller VCP ChokecoilTemp. Avg. [°C] is highly imbalanced (77.4%) Imbalance
Controller VCP WaterTemp. Avg. [°C] is highly imbalanced (50.4%) Imbalance
Blades PitchAngle Min. [°] is highly imbalanced (58.5%) Imbalance
Blades PitchAngle Max. [°] is highly imbalanced (56.4%) Imbalance
Blades PitchAngle Avg. [°] is highly imbalanced (56.0%) Imbalance
Blades PitchAngle StdDev [°] is highly imbalanced (51.1%) Imbalance
HVTrafo Phase1 Temp. Avg. [°C] is highly imbalanced (83.0%) Imbalance
HVTrafo Phase2 Temp. Avg. [°C] is highly imbalanced (83.7%) Imbalance
HVTrafo Phase3 Temp. Avg. [°C] is highly imbalanced (80.5%) Imbalance
HVTrafo AirOutlet Temp. Avg. [°C] is highly imbalanced (56.2%) Imbalance
HourCounters Average GridOn Avg. [h] is highly imbalanced (95.8%) Imbalance
HourCounters Average GridOk Avg. [h] is highly imbalanced (96.2%) Imbalance
HourCounters Average TurbineOk Avg. [h] is highly imbalanced (96.6%) Imbalance
HourCounters Average Run Avg. [h] is highly imbalanced (95.7%) Imbalance
HourCounters Average Gen1 Avg. [h] is highly imbalanced (83.2%) Imbalance
HourCounters Average Gen2 Avg. [h] is highly imbalanced (65.8%) Imbalance
HourCounters Average Yaw Avg. [h] is highly imbalanced (53.4%) Imbalance
HourCounters Average ServiceOn Avg. [h] is highly imbalanced (98.1%) Imbalance
HourCounters Average AmbientOk Avg. [h] is highly imbalanced (94.5%) Imbalance
HourCounters Average WindOk Avg. [h] is highly imbalanced (65.1%) Imbalance
HourCounters Average AlarmActive Avg. [h] is highly imbalanced (94.4%) Imbalance
Production LatestAverage Active Power Gen 0 Avg. [W] is highly imbalanced (68.3%) Imbalance
Production LatestAverage Active Power Gen 1 Avg. [W] is highly imbalanced (86.9%) Imbalance
Production LatestAverage Active Power Gen 2 Avg. [W] is highly imbalanced (77.7%) Imbalance
Production LatestAverage Total Active Power Avg. [W] is highly imbalanced (77.1%) Imbalance
Production LatestAverage Reactive Power Gen 0 Avg. [var] is highly imbalanced (66.2%) Imbalance
Production LatestAverage Reactive Power Gen 1 Avg. [var] is highly imbalanced (63.2%) Imbalance
Production LatestAverage Reactive Power Gen 2 Avg. [var] is highly imbalanced (61.0%) Imbalance
Active power generator 2, Total accumulated [W] is highly imbalanced (99.9%) Imbalance
Total Active power [W] is highly imbalanced (99.8%) Imbalance
Reactive power generator 0,Total accumulated [var] is highly imbalanced (96.0%) Imbalance
Total reactive power [var] is highly imbalanced (94.2%) Imbalance
Timestamp has unique values Unique

Reproduction

Analysis started2025-05-15 12:08:43.686120
Analysis finished2025-05-15 12:09:13.591930
Duration29.91 seconds
Software versionydata-profiling vv4.16.1
Download configurationconfig.json

Variables

Timestamp
Date

Unique 

Distinct26208
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.4 MiB
Minimum2020-01-01 00:00:00
Maximum2020-06-30 23:50:00
Invalid dates0
Invalid dates (%)0.0%
2025-05-15T14:09:13.632448image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-15T14:09:13.716055image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Generator RPM Max. [RPM]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24259 
1
 
1949

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24259
92.6%
1 1949
 
7.4%

Length

2025-05-15T14:09:13.791002image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:13.827956image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24259
92.6%
1 1949
 
7.4%

Most occurring characters

ValueCountFrequency (%)
0 24259
92.6%
1 1949
 
7.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24259
92.6%
1 1949
 
7.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24259
92.6%
1 1949
 
7.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24259
92.6%
1 1949
 
7.4%

Generator RPM Min. [RPM]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23674 
1
2534 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23674
90.3%
1 2534
 
9.7%

Length

2025-05-15T14:09:13.870320image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:13.906996image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23674
90.3%
1 2534
 
9.7%

Most occurring characters

ValueCountFrequency (%)
0 23674
90.3%
1 2534
 
9.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23674
90.3%
1 2534
 
9.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23674
90.3%
1 2534
 
9.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23674
90.3%
1 2534
 
9.7%

Generator RPM Avg. [RPM]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23971 
1
 
2237

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23971
91.5%
1 2237
 
8.5%

Length

2025-05-15T14:09:13.953060image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:13.990137image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23971
91.5%
1 2237
 
8.5%

Most occurring characters

ValueCountFrequency (%)
0 23971
91.5%
1 2237
 
8.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23971
91.5%
1 2237
 
8.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23971
91.5%
1 2237
 
8.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23971
91.5%
1 2237
 
8.5%

Generator RPM StdDev [RPM]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23952 
1
 
2256

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23952
91.4%
1 2256
 
8.6%

Length

2025-05-15T14:09:14.034342image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:14.072258image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23952
91.4%
1 2256
 
8.6%

Most occurring characters

ValueCountFrequency (%)
0 23952
91.4%
1 2256
 
8.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23952
91.4%
1 2256
 
8.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23952
91.4%
1 2256
 
8.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23952
91.4%
1 2256
 
8.6%

Generator Bearing Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25232 
1
 
976

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25232
96.3%
1 976
 
3.7%

Length

2025-05-15T14:09:14.116853image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:14.152669image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25232
96.3%
1 976
 
3.7%

Most occurring characters

ValueCountFrequency (%)
0 25232
96.3%
1 976
 
3.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25232
96.3%
1 976
 
3.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25232
96.3%
1 976
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25232
96.3%
1 976
 
3.7%

Generator Phase1 Temp. Avg. [°C]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25187 
1
 
1021

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25187
96.1%
1 1021
 
3.9%

Length

2025-05-15T14:09:14.196671image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:14.232538image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25187
96.1%
1 1021
 
3.9%

Most occurring characters

ValueCountFrequency (%)
0 25187
96.1%
1 1021
 
3.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25187
96.1%
1 1021
 
3.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25187
96.1%
1 1021
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25187
96.1%
1 1021
 
3.9%

Generator Phase2 Temp. Avg. [°C]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25288 
1
 
920

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25288
96.5%
1 920
 
3.5%

Length

2025-05-15T14:09:14.275138image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:14.312548image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25288
96.5%
1 920
 
3.5%

Most occurring characters

ValueCountFrequency (%)
0 25288
96.5%
1 920
 
3.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25288
96.5%
1 920
 
3.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25288
96.5%
1 920
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25288
96.5%
1 920
 
3.5%

Generator Phase3 Temp. Avg. [°C]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25357 
1
 
851

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25357
96.8%
1 851
 
3.2%

Length

2025-05-15T14:09:14.355217image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:14.391121image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25357
96.8%
1 851
 
3.2%

Most occurring characters

ValueCountFrequency (%)
0 25357
96.8%
1 851
 
3.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25357
96.8%
1 851
 
3.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25357
96.8%
1 851
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25357
96.8%
1 851
 
3.2%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23844 
1
 
2364

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23844
91.0%
1 2364
 
9.0%

Length

2025-05-15T14:09:14.435627image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:14.472494image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23844
91.0%
1 2364
 
9.0%

Most occurring characters

ValueCountFrequency (%)
0 23844
91.0%
1 2364
 
9.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23844
91.0%
1 2364
 
9.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23844
91.0%
1 2364
 
9.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23844
91.0%
1 2364
 
9.0%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25318 
1
 
890

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25318
96.6%
1 890
 
3.4%

Length

2025-05-15T14:09:14.516971image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:14.554497image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25318
96.6%
1 890
 
3.4%

Most occurring characters

ValueCountFrequency (%)
0 25318
96.6%
1 890
 
3.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25318
96.6%
1 890
 
3.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25318
96.6%
1 890
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25318
96.6%
1 890
 
3.4%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
22621 
1
3587 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 22621
86.3%
1 3587
 
13.7%

Length

2025-05-15T14:09:14.597647image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:14.635327image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 22621
86.3%
1 3587
 
13.7%

Most occurring characters

ValueCountFrequency (%)
0 22621
86.3%
1 3587
 
13.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 22621
86.3%
1 3587
 
13.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 22621
86.3%
1 3587
 
13.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 22621
86.3%
1 3587
 
13.7%

Hydraulic Oil Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25533 
1
 
675

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25533
97.4%
1 675
 
2.6%

Length

2025-05-15T14:09:14.683647image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:14.719673image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25533
97.4%
1 675
 
2.6%

Most occurring characters

ValueCountFrequency (%)
0 25533
97.4%
1 675
 
2.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25533
97.4%
1 675
 
2.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25533
97.4%
1 675
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25533
97.4%
1 675
 
2.6%

Gear Oil Temp. Avg. [°C]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:09:14.762575image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:14.798023image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Gear Bearing Temp. Avg. [°C]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:09:14.837799image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:14.871578image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24479 
1
 
1729

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24479
93.4%
1 1729
 
6.6%

Length

2025-05-15T14:09:14.912905image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:14.948920image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24479
93.4%
1 1729
 
6.6%

Most occurring characters

ValueCountFrequency (%)
0 24479
93.4%
1 1729
 
6.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24479
93.4%
1 1729
 
6.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24479
93.4%
1 1729
 
6.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24479
93.4%
1 1729
 
6.6%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24863 
1
 
1345

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24863
94.9%
1 1345
 
5.1%

Length

2025-05-15T14:09:14.991833image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:15.029704image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24863
94.9%
1 1345
 
5.1%

Most occurring characters

ValueCountFrequency (%)
0 24863
94.9%
1 1345
 
5.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24863
94.9%
1 1345
 
5.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24863
94.9%
1 1345
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24863
94.9%
1 1345
 
5.1%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:09:15.072181image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:15.106147image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25279 
1
 
929

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25279
96.5%
1 929
 
3.5%

Length

2025-05-15T14:09:15.147540image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:15.183509image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25279
96.5%
1 929
 
3.5%

Most occurring characters

ValueCountFrequency (%)
0 25279
96.5%
1 929
 
3.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25279
96.5%
1 929
 
3.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25279
96.5%
1 929
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25279
96.5%
1 929
 
3.5%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25125 
1
 
1083

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25125
95.9%
1 1083
 
4.1%

Length

2025-05-15T14:09:15.226149image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:15.263934image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25125
95.9%
1 1083
 
4.1%

Most occurring characters

ValueCountFrequency (%)
0 25125
95.9%
1 1083
 
4.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25125
95.9%
1 1083
 
4.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25125
95.9%
1 1083
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25125
95.9%
1 1083
 
4.1%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24909 
1
 
1299

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24909
95.0%
1 1299
 
5.0%

Length

2025-05-15T14:09:15.306534image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:15.342572image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24909
95.0%
1 1299
 
5.0%

Most occurring characters

ValueCountFrequency (%)
0 24909
95.0%
1 1299
 
5.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24909
95.0%
1 1299
 
5.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24909
95.0%
1 1299
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24909
95.0%
1 1299
 
5.0%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24238 
1
 
1970

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24238
92.5%
1 1970
 
7.5%

Length

2025-05-15T14:09:15.568337image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:15.604545image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24238
92.5%
1 1970
 
7.5%

Most occurring characters

ValueCountFrequency (%)
0 24238
92.5%
1 1970
 
7.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24238
92.5%
1 1970
 
7.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24238
92.5%
1 1970
 
7.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24238
92.5%
1 1970
 
7.5%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24483 
1
 
1725

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24483
93.4%
1 1725
 
6.6%

Length

2025-05-15T14:09:15.646722image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:15.684570image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24483
93.4%
1 1725
 
6.6%

Most occurring characters

ValueCountFrequency (%)
0 24483
93.4%
1 1725
 
6.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24483
93.4%
1 1725
 
6.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24483
93.4%
1 1725
 
6.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24483
93.4%
1 1725
 
6.6%

Nacelle Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23866 
1
 
2342

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23866
91.1%
1 2342
 
8.9%

Length

2025-05-15T14:09:15.727087image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:15.763526image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23866
91.1%
1 2342
 
8.9%

Most occurring characters

ValueCountFrequency (%)
0 23866
91.1%
1 2342
 
8.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23866
91.1%
1 2342
 
8.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23866
91.1%
1 2342
 
8.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23866
91.1%
1 2342
 
8.9%

Rotor RPM Max. [RPM]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23480 
1
2728 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23480
89.6%
1 2728
 
10.4%

Length

2025-05-15T14:09:15.809833image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:15.846185image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23480
89.6%
1 2728
 
10.4%

Most occurring characters

ValueCountFrequency (%)
0 23480
89.6%
1 2728
 
10.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23480
89.6%
1 2728
 
10.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23480
89.6%
1 2728
 
10.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23480
89.6%
1 2728
 
10.4%

Rotor RPM Min. [RPM]
Categorical

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23228 
1
2980 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23228
88.6%
1 2980
 
11.4%

Length

2025-05-15T14:09:15.890634image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:15.928639image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23228
88.6%
1 2980
 
11.4%

Most occurring characters

ValueCountFrequency (%)
0 23228
88.6%
1 2980
 
11.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23228
88.6%
1 2980
 
11.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23228
88.6%
1 2980
 
11.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23228
88.6%
1 2980
 
11.4%

Rotor RPM Avg. [RPM]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23840 
1
 
2368

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23840
91.0%
1 2368
 
9.0%

Length

2025-05-15T14:09:15.973439image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:16.010135image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23840
91.0%
1 2368
 
9.0%

Most occurring characters

ValueCountFrequency (%)
0 23840
91.0%
1 2368
 
9.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23840
91.0%
1 2368
 
9.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23840
91.0%
1 2368
 
9.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23840
91.0%
1 2368
 
9.0%

Rotor RPM StdDev [RPM]
Categorical

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23167 
1
3041 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23167
88.4%
1 3041
 
11.6%

Length

2025-05-15T14:09:16.056185image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:16.092727image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23167
88.4%
1 3041
 
11.6%

Most occurring characters

ValueCountFrequency (%)
0 23167
88.4%
1 3041
 
11.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23167
88.4%
1 3041
 
11.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23167
88.4%
1 3041
 
11.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23167
88.4%
1 3041
 
11.6%

Ambient WindSpeed Max. [m/s]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25853 
1
 
355

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25853
98.6%
1 355
 
1.4%

Length

2025-05-15T14:09:16.138520image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:16.174533image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25853
98.6%
1 355
 
1.4%

Most occurring characters

ValueCountFrequency (%)
0 25853
98.6%
1 355
 
1.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25853
98.6%
1 355
 
1.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25853
98.6%
1 355
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25853
98.6%
1 355
 
1.4%

Ambient WindSpeed Min. [m/s]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25673 
1
 
535

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25673
98.0%
1 535
 
2.0%

Length

2025-05-15T14:09:16.216904image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:16.254203image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25673
98.0%
1 535
 
2.0%

Most occurring characters

ValueCountFrequency (%)
0 25673
98.0%
1 535
 
2.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25673
98.0%
1 535
 
2.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25673
98.0%
1 535
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25673
98.0%
1 535
 
2.0%

Ambient WindSpeed Avg. [m/s]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25938 
1
 
270

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25938
99.0%
1 270
 
1.0%

Length

2025-05-15T14:09:16.296915image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:16.332802image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25938
99.0%
1 270
 
1.0%

Most occurring characters

ValueCountFrequency (%)
0 25938
99.0%
1 270
 
1.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25938
99.0%
1 270
 
1.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25938
99.0%
1 270
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25938
99.0%
1 270
 
1.0%

Ambient WindSpeed StdDev [m/s]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24811 
1
 
1397

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24811
94.7%
1 1397
 
5.3%

Length

2025-05-15T14:09:16.377153image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:16.413068image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24811
94.7%
1 1397
 
5.3%

Most occurring characters

ValueCountFrequency (%)
0 24811
94.7%
1 1397
 
5.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24811
94.7%
1 1397
 
5.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24811
94.7%
1 1397
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24811
94.7%
1 1397
 
5.3%

Ambient WindDir Relative Avg. [°]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25421 
1
 
787

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25421
97.0%
1 787
 
3.0%

Length

2025-05-15T14:09:16.455581image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:16.493988image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25421
97.0%
1 787
 
3.0%

Most occurring characters

ValueCountFrequency (%)
0 25421
97.0%
1 787
 
3.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25421
97.0%
1 787
 
3.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25421
97.0%
1 787
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25421
97.0%
1 787
 
3.0%

Ambient WindDir Absolute Avg. [°]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25601 
1
 
607

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25601
97.7%
1 607
 
2.3%

Length

2025-05-15T14:09:16.536267image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:16.572146image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25601
97.7%
1 607
 
2.3%

Most occurring characters

ValueCountFrequency (%)
0 25601
97.7%
1 607
 
2.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25601
97.7%
1 607
 
2.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25601
97.7%
1 607
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25601
97.7%
1 607
 
2.3%

Ambient Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23403 
1
2805 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23403
89.3%
1 2805
 
10.7%

Length

2025-05-15T14:09:16.616520image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:16.653270image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23403
89.3%
1 2805
 
10.7%

Most occurring characters

ValueCountFrequency (%)
0 23403
89.3%
1 2805
 
10.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23403
89.3%
1 2805
 
10.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23403
89.3%
1 2805
 
10.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23403
89.3%
1 2805
 
10.7%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:09:16.697942image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:16.733363image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24519 
1
 
1689

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24519
93.6%
1 1689
 
6.4%

Length

2025-05-15T14:09:16.773214image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:16.809228image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24519
93.6%
1 1689
 
6.4%

Most occurring characters

ValueCountFrequency (%)
0 24519
93.6%
1 1689
 
6.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24519
93.6%
1 1689
 
6.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24519
93.6%
1 1689
 
6.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24519
93.6%
1 1689
 
6.4%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24109 
1
 
2099

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24109
92.0%
1 2099
 
8.0%

Length

2025-05-15T14:09:16.853330image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:16.889919image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24109
92.0%
1 2099
 
8.0%

Most occurring characters

ValueCountFrequency (%)
0 24109
92.0%
1 2099
 
8.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24109
92.0%
1 2099
 
8.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24109
92.0%
1 2099
 
8.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24109
92.0%
1 2099
 
8.0%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23871 
1
 
2337

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23871
91.1%
1 2337
 
8.9%

Length

2025-05-15T14:09:16.934409image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:16.972667image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23871
91.1%
1 2337
 
8.9%

Most occurring characters

ValueCountFrequency (%)
0 23871
91.1%
1 2337
 
8.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23871
91.1%
1 2337
 
8.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23871
91.1%
1 2337
 
8.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23871
91.1%
1 2337
 
8.9%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23961 
1
 
2247

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23961
91.4%
1 2247
 
8.6%

Length

2025-05-15T14:09:17.017115image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:17.053802image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23961
91.4%
1 2247
 
8.6%

Most occurring characters

ValueCountFrequency (%)
0 23961
91.4%
1 2247
 
8.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23961
91.4%
1 2247
 
8.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23961
91.4%
1 2247
 
8.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23961
91.4%
1 2247
 
8.6%

Grid Production Power Avg. [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25123 
1
 
1085

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25123
95.9%
1 1085
 
4.1%

Length

2025-05-15T14:09:17.100163image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:17.136448image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25123
95.9%
1 1085
 
4.1%

Most occurring characters

ValueCountFrequency (%)
0 25123
95.9%
1 1085
 
4.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25123
95.9%
1 1085
 
4.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25123
95.9%
1 1085
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25123
95.9%
1 1085
 
4.1%

Grid Production CosPhi Avg.
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24687 
1
 
1521

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24687
94.2%
1 1521
 
5.8%

Length

2025-05-15T14:09:17.179060image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:17.217011image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24687
94.2%
1 1521
 
5.8%

Most occurring characters

ValueCountFrequency (%)
0 24687
94.2%
1 1521
 
5.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24687
94.2%
1 1521
 
5.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24687
94.2%
1 1521
 
5.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24687
94.2%
1 1521
 
5.8%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26084 
1
 
124

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26084
99.5%
1 124
 
0.5%

Length

2025-05-15T14:09:17.259594image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:17.295840image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26084
99.5%
1 124
 
0.5%

Most occurring characters

ValueCountFrequency (%)
0 26084
99.5%
1 124
 
0.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26084
99.5%
1 124
 
0.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26084
99.5%
1 124
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26084
99.5%
1 124
 
0.5%

Grid Production VoltagePhase1 Avg. [V]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25974 
1
 
234

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25974
99.1%
1 234
 
0.9%

Length

2025-05-15T14:09:17.340150image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:17.376116image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25974
99.1%
1 234
 
0.9%

Most occurring characters

ValueCountFrequency (%)
0 25974
99.1%
1 234
 
0.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25974
99.1%
1 234
 
0.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25974
99.1%
1 234
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25974
99.1%
1 234
 
0.9%

Grid Production VoltagePhase2 Avg. [V]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25949 
1
 
259

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25949
99.0%
1 259
 
1.0%

Length

2025-05-15T14:09:17.418731image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:17.456416image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25949
99.0%
1 259
 
1.0%

Most occurring characters

ValueCountFrequency (%)
0 25949
99.0%
1 259
 
1.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25949
99.0%
1 259
 
1.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25949
99.0%
1 259
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25949
99.0%
1 259
 
1.0%

Grid Production VoltagePhase3 Avg. [V]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25928 
1
 
280

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25928
98.9%
1 280
 
1.1%

Length

2025-05-15T14:09:17.501150image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:17.537256image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25928
98.9%
1 280
 
1.1%

Most occurring characters

ValueCountFrequency (%)
0 25928
98.9%
1 280
 
1.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25928
98.9%
1 280
 
1.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25928
98.9%
1 280
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25928
98.9%
1 280
 
1.1%

Grid Production CurrentPhase1 Avg. [A]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25081 
1
 
1127

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25081
95.7%
1 1127
 
4.3%

Length

2025-05-15T14:09:17.581785image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:17.617757image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25081
95.7%
1 1127
 
4.3%

Most occurring characters

ValueCountFrequency (%)
0 25081
95.7%
1 1127
 
4.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25081
95.7%
1 1127
 
4.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25081
95.7%
1 1127
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25081
95.7%
1 1127
 
4.3%

Grid Production CurrentPhase2 Avg. [A]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25085 
1
 
1123

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25085
95.7%
1 1123
 
4.3%

Length

2025-05-15T14:09:17.660207image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:17.698116image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25085
95.7%
1 1123
 
4.3%

Most occurring characters

ValueCountFrequency (%)
0 25085
95.7%
1 1123
 
4.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25085
95.7%
1 1123
 
4.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25085
95.7%
1 1123
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25085
95.7%
1 1123
 
4.3%

Grid Production CurrentPhase3 Avg. [A]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25148 
1
 
1060

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25148
96.0%
1 1060
 
4.0%

Length

2025-05-15T14:09:17.740910image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:17.776949image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25148
96.0%
1 1060
 
4.0%

Most occurring characters

ValueCountFrequency (%)
0 25148
96.0%
1 1060
 
4.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25148
96.0%
1 1060
 
4.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25148
96.0%
1 1060
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25148
96.0%
1 1060
 
4.0%

Grid Production Power Max. [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24691 
1
 
1517

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24691
94.2%
1 1517
 
5.8%

Length

2025-05-15T14:09:17.822043image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:17.858138image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24691
94.2%
1 1517
 
5.8%

Most occurring characters

ValueCountFrequency (%)
0 24691
94.2%
1 1517
 
5.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24691
94.2%
1 1517
 
5.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24691
94.2%
1 1517
 
5.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24691
94.2%
1 1517
 
5.8%

Grid Production Power Min. [W]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24576 
1
 
1632

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24576
93.8%
1 1632
 
6.2%

Length

2025-05-15T14:09:17.900759image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:17.938520image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24576
93.8%
1 1632
 
6.2%

Most occurring characters

ValueCountFrequency (%)
0 24576
93.8%
1 1632
 
6.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24576
93.8%
1 1632
 
6.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24576
93.8%
1 1632
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24576
93.8%
1 1632
 
6.2%

Grid Busbar Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25044 
1
 
1164

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25044
95.6%
1 1164
 
4.4%

Length

2025-05-15T14:09:17.981222image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:18.017393image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25044
95.6%
1 1164
 
4.4%

Most occurring characters

ValueCountFrequency (%)
0 25044
95.6%
1 1164
 
4.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25044
95.6%
1 1164
 
4.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25044
95.6%
1 1164
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25044
95.6%
1 1164
 
4.4%

Grid Production Power StdDev [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24937 
1
 
1271

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24937
95.2%
1 1271
 
4.8%

Length

2025-05-15T14:09:18.062217image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:18.098298image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24937
95.2%
1 1271
 
4.8%

Most occurring characters

ValueCountFrequency (%)
0 24937
95.2%
1 1271
 
4.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24937
95.2%
1 1271
 
4.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24937
95.2%
1 1271
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24937
95.2%
1 1271
 
4.8%

Grid Production ReactivePower Avg. [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23969 
1
 
2239

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23969
91.5%
1 2239
 
8.5%

Length

2025-05-15T14:09:18.141050image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:18.179699image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23969
91.5%
1 2239
 
8.5%

Most occurring characters

ValueCountFrequency (%)
0 23969
91.5%
1 2239
 
8.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23969
91.5%
1 2239
 
8.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23969
91.5%
1 2239
 
8.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23969
91.5%
1 2239
 
8.5%

Grid Production ReactivePower Max. [W]
Categorical

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
22353 
1
3855 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 22353
85.3%
1 3855
 
14.7%

Length

2025-05-15T14:09:18.224282image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:18.261103image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 22353
85.3%
1 3855
 
14.7%

Most occurring characters

ValueCountFrequency (%)
0 22353
85.3%
1 3855
 
14.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 22353
85.3%
1 3855
 
14.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 22353
85.3%
1 3855
 
14.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 22353
85.3%
1 3855
 
14.7%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
22158 
1
4050 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 22158
84.5%
1 4050
 
15.5%

Length

2025-05-15T14:09:18.307528image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:18.344410image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 22158
84.5%
1 4050
 
15.5%

Most occurring characters

ValueCountFrequency (%)
0 22158
84.5%
1 4050
 
15.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 22158
84.5%
1 4050
 
15.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 22158
84.5%
1 4050
 
15.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 22158
84.5%
1 4050
 
15.5%

Grid Production ReactivePower StdDev [W]
Categorical

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
22757 
1
3451 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 22757
86.8%
1 3451
 
13.2%

Length

2025-05-15T14:09:18.388753image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:18.576586image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 22757
86.8%
1 3451
 
13.2%

Most occurring characters

ValueCountFrequency (%)
0 22757
86.8%
1 3451
 
13.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 22757
86.8%
1 3451
 
13.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 22757
86.8%
1 3451
 
13.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 22757
86.8%
1 3451
 
13.2%

Grid Production PossiblePower Avg. [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25510 
1
 
698

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25510
97.3%
1 698
 
2.7%

Length

2025-05-15T14:09:18.621179image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:18.657096image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25510
97.3%
1 698
 
2.7%

Most occurring characters

ValueCountFrequency (%)
0 25510
97.3%
1 698
 
2.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25510
97.3%
1 698
 
2.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25510
97.3%
1 698
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25510
97.3%
1 698
 
2.7%

Grid Production PossiblePower Max. [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25301 
1
 
907

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25301
96.5%
1 907
 
3.5%

Length

2025-05-15T14:09:18.701563image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:18.737306image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25301
96.5%
1 907
 
3.5%

Most occurring characters

ValueCountFrequency (%)
0 25301
96.5%
1 907
 
3.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25301
96.5%
1 907
 
3.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25301
96.5%
1 907
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25301
96.5%
1 907
 
3.5%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25122 
1
 
1086

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25122
95.9%
1 1086
 
4.1%

Length

2025-05-15T14:09:18.779722image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:18.817537image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25122
95.9%
1 1086
 
4.1%

Most occurring characters

ValueCountFrequency (%)
0 25122
95.9%
1 1086
 
4.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25122
95.9%
1 1086
 
4.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25122
95.9%
1 1086
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25122
95.9%
1 1086
 
4.1%

Grid Production PossiblePower StdDev [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25308 
1
 
900

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25308
96.6%
1 900
 
3.4%

Length

2025-05-15T14:09:18.859917image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:18.896017image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25308
96.6%
1 900
 
3.4%

Most occurring characters

ValueCountFrequency (%)
0 25308
96.6%
1 900
 
3.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25308
96.6%
1 900
 
3.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25308
96.6%
1 900
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25308
96.6%
1 900
 
3.4%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:09:18.940670image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:18.974237image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:09:19.013957image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:19.049463image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:09:19.089283image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:19.122786image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:09:19.164179image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:19.197709image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:09:19.237082image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:19.272306image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:09:19.311655image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:19.345077image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:09:19.386074image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:19.419688image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:09:19.461091image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:19.494602image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Active power limit [W]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25795 
1
 
413

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25795
98.4%
1 413
 
1.6%

Length

2025-05-15T14:09:19.534442image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:19.570022image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25795
98.4%
1 413
 
1.6%

Most occurring characters

ValueCountFrequency (%)
0 25795
98.4%
1 413
 
1.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25795
98.4%
1 413
 
1.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25795
98.4%
1 413
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25795
98.4%
1 413
 
1.6%

Active power limit source
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26151 
1
 
57

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26151
99.8%
1 57
 
0.2%

Length

2025-05-15T14:09:19.614256image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:19.650297image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26151
99.8%
1 57
 
0.2%

Most occurring characters

ValueCountFrequency (%)
0 26151
99.8%
1 57
 
0.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26151
99.8%
1 57
 
0.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26151
99.8%
1 57
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26151
99.8%
1 57
 
0.2%

Reactive power set point [var]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:09:19.694896image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:19.728615image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Power factor set point
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26151 
1
 
57

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26151
99.8%
1 57
 
0.2%

Length

2025-05-15T14:09:19.768088image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:19.803815image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26151
99.8%
1 57
 
0.2%

Most occurring characters

ValueCountFrequency (%)
0 26151
99.8%
1 57
 
0.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26151
99.8%
1 57
 
0.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26151
99.8%
1 57
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26151
99.8%
1 57
 
0.2%

Power factor set point source
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26151 
1
 
57

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26151
99.8%
1 57
 
0.2%

Length

2025-05-15T14:09:19.848380image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:19.884218image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26151
99.8%
1 57
 
0.2%

Most occurring characters

ValueCountFrequency (%)
0 26151
99.8%
1 57
 
0.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26151
99.8%
1 57
 
0.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26151
99.8%
1 57
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26151
99.8%
1 57
 
0.2%

Controller Ground Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25698 
1
 
510

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25698
98.1%
1 510
 
1.9%

Length

2025-05-15T14:09:19.928650image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:19.964578image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25698
98.1%
1 510
 
1.9%

Most occurring characters

ValueCountFrequency (%)
0 25698
98.1%
1 510
 
1.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25698
98.1%
1 510
 
1.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25698
98.1%
1 510
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25698
98.1%
1 510
 
1.9%

Controller Top Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24793 
1
 
1415

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24793
94.6%
1 1415
 
5.4%

Length

2025-05-15T14:09:20.007189image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:20.042870image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24793
94.6%
1 1415
 
5.4%

Most occurring characters

ValueCountFrequency (%)
0 24793
94.6%
1 1415
 
5.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24793
94.6%
1 1415
 
5.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24793
94.6%
1 1415
 
5.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24793
94.6%
1 1415
 
5.4%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
22950 
1
3258 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 22950
87.6%
1 3258
 
12.4%

Length

2025-05-15T14:09:20.087459image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:20.123817image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 22950
87.6%
1 3258
 
12.4%

Most occurring characters

ValueCountFrequency (%)
0 22950
87.6%
1 3258
 
12.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 22950
87.6%
1 3258
 
12.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 22950
87.6%
1 3258
 
12.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 22950
87.6%
1 3258
 
12.4%

Controller VCP Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24064 
1
 
2144

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24064
91.8%
1 2144
 
8.2%

Length

2025-05-15T14:09:20.170499image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:20.207027image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24064
91.8%
1 2144
 
8.2%

Most occurring characters

ValueCountFrequency (%)
0 24064
91.8%
1 2144
 
8.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24064
91.8%
1 2144
 
8.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24064
91.8%
1 2144
 
8.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24064
91.8%
1 2144
 
8.2%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25252 
1
 
956

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25252
96.4%
1 956
 
3.6%

Length

2025-05-15T14:09:20.251233image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:20.286853image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25252
96.4%
1 956
 
3.6%

Most occurring characters

ValueCountFrequency (%)
0 25252
96.4%
1 956
 
3.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25252
96.4%
1 956
 
3.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25252
96.4%
1 956
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25252
96.4%
1 956
 
3.6%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23356 
1
2852 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23356
89.1%
1 2852
 
10.9%

Length

2025-05-15T14:09:20.331195image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:20.367775image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23356
89.1%
1 2852
 
10.9%

Most occurring characters

ValueCountFrequency (%)
0 23356
89.1%
1 2852
 
10.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23356
89.1%
1 2852
 
10.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23356
89.1%
1 2852
 
10.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23356
89.1%
1 2852
 
10.9%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23270 
1
2938 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23270
88.8%
1 2938
 
11.2%

Length

2025-05-15T14:09:20.413910image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:20.450705image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23270
88.8%
1 2938
 
11.2%

Most occurring characters

ValueCountFrequency (%)
0 23270
88.8%
1 2938
 
11.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23270
88.8%
1 2938
 
11.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23270
88.8%
1 2938
 
11.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23270
88.8%
1 2938
 
11.2%

Spinner Temp. SlipRing Avg. [°C]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:09:20.495125image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:20.528824image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Blades PitchAngle Min. [°]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24013 
1
 
2195

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24013
91.6%
1 2195
 
8.4%

Length

2025-05-15T14:09:20.570234image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:20.606805image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24013
91.6%
1 2195
 
8.4%

Most occurring characters

ValueCountFrequency (%)
0 24013
91.6%
1 2195
 
8.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24013
91.6%
1 2195
 
8.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24013
91.6%
1 2195
 
8.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24013
91.6%
1 2195
 
8.4%

Blades PitchAngle Max. [°]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23853 
1
 
2355

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23853
91.0%
1 2355
 
9.0%

Length

2025-05-15T14:09:20.651302image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:20.689829image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23853
91.0%
1 2355
 
9.0%

Most occurring characters

ValueCountFrequency (%)
0 23853
91.0%
1 2355
 
9.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23853
91.0%
1 2355
 
9.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23853
91.0%
1 2355
 
9.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23853
91.0%
1 2355
 
9.0%

Blades PitchAngle Avg. [°]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23822 
1
2386 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23822
90.9%
1 2386
 
9.1%

Length

2025-05-15T14:09:20.734386image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:20.770811image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23822
90.9%
1 2386
 
9.1%

Most occurring characters

ValueCountFrequency (%)
0 23822
90.9%
1 2386
 
9.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23822
90.9%
1 2386
 
9.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23822
90.9%
1 2386
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23822
90.9%
1 2386
 
9.1%

Blades PitchAngle StdDev [°]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23418 
1
2790 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23418
89.4%
1 2790
 
10.6%

Length

2025-05-15T14:09:20.817182image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:20.854273image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23418
89.4%
1 2790
 
10.6%

Most occurring characters

ValueCountFrequency (%)
0 23418
89.4%
1 2790
 
10.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23418
89.4%
1 2790
 
10.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23418
89.4%
1 2790
 
10.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23418
89.4%
1 2790
 
10.6%

HVTrafo Phase1 Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25548 
1
 
660

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25548
97.5%
1 660
 
2.5%

Length

2025-05-15T14:09:20.901738image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:20.937819image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25548
97.5%
1 660
 
2.5%

Most occurring characters

ValueCountFrequency (%)
0 25548
97.5%
1 660
 
2.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25548
97.5%
1 660
 
2.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25548
97.5%
1 660
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25548
97.5%
1 660
 
2.5%

HVTrafo Phase2 Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25581 
1
 
627

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25581
97.6%
1 627
 
2.4%

Length

2025-05-15T14:09:20.980258image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:21.015942image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25581
97.6%
1 627
 
2.4%

Most occurring characters

ValueCountFrequency (%)
0 25581
97.6%
1 627
 
2.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25581
97.6%
1 627
 
2.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25581
97.6%
1 627
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25581
97.6%
1 627
 
2.4%

HVTrafo Phase3 Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25417 
1
 
791

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25417
97.0%
1 791
 
3.0%

Length

2025-05-15T14:09:21.060229image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:21.096443image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25417
97.0%
1 791
 
3.0%

Most occurring characters

ValueCountFrequency (%)
0 25417
97.0%
1 791
 
3.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25417
97.0%
1 791
 
3.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25417
97.0%
1 791
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25417
97.0%
1 791
 
3.0%

HVTrafo AirOutlet Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23834 
1
 
2374

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23834
90.9%
1 2374
 
9.1%

Length

2025-05-15T14:09:21.140578image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:21.329964image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23834
90.9%
1 2374
 
9.1%

Most occurring characters

ValueCountFrequency (%)
0 23834
90.9%
1 2374
 
9.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23834
90.9%
1 2374
 
9.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23834
90.9%
1 2374
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23834
90.9%
1 2374
 
9.1%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:09:21.374293image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:21.408011image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

HourCounters Average GridOn Avg. [h]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26087 
1
 
121

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26087
99.5%
1 121
 
0.5%

Length

2025-05-15T14:09:21.448791image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:21.484393image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26087
99.5%
1 121
 
0.5%

Most occurring characters

ValueCountFrequency (%)
0 26087
99.5%
1 121
 
0.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26087
99.5%
1 121
 
0.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26087
99.5%
1 121
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26087
99.5%
1 121
 
0.5%

HourCounters Average GridOk Avg. [h]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26102 
1
 
106

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26102
99.6%
1 106
 
0.4%

Length

2025-05-15T14:09:21.528783image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:21.564702image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26102
99.6%
1 106
 
0.4%

Most occurring characters

ValueCountFrequency (%)
0 26102
99.6%
1 106
 
0.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26102
99.6%
1 106
 
0.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26102
99.6%
1 106
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26102
99.6%
1 106
 
0.4%

HourCounters Average TurbineOk Avg. [h]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26116 
1
 
92

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26116
99.6%
1 92
 
0.4%

Length

2025-05-15T14:09:21.607224image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:21.644778image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26116
99.6%
1 92
 
0.4%

Most occurring characters

ValueCountFrequency (%)
0 26116
99.6%
1 92
 
0.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26116
99.6%
1 92
 
0.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26116
99.6%
1 92
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26116
99.6%
1 92
 
0.4%

HourCounters Average Run Avg. [h]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26085 
1
 
123

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26085
99.5%
1 123
 
0.5%

Length

2025-05-15T14:09:21.687162image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:21.723368image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26085
99.5%
1 123
 
0.5%

Most occurring characters

ValueCountFrequency (%)
0 26085
99.5%
1 123
 
0.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26085
99.5%
1 123
 
0.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26085
99.5%
1 123
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26085
99.5%
1 123
 
0.5%

HourCounters Average Gen1 Avg. [h]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25554 
1
 
654

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25554
97.5%
1 654
 
2.5%

Length

2025-05-15T14:09:21.767922image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:21.804153image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25554
97.5%
1 654
 
2.5%

Most occurring characters

ValueCountFrequency (%)
0 25554
97.5%
1 654
 
2.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25554
97.5%
1 654
 
2.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25554
97.5%
1 654
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25554
97.5%
1 654
 
2.5%

HourCounters Average Gen2 Avg. [h]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24537 
1
 
1671

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24537
93.6%
1 1671
 
6.4%

Length

2025-05-15T14:09:21.846753image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:21.884543image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24537
93.6%
1 1671
 
6.4%

Most occurring characters

ValueCountFrequency (%)
0 24537
93.6%
1 1671
 
6.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24537
93.6%
1 1671
 
6.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24537
93.6%
1 1671
 
6.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24537
93.6%
1 1671
 
6.4%

HourCounters Average Yaw Avg. [h]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23611 
1
2597 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23611
90.1%
1 2597
 
9.9%

Length

2025-05-15T14:09:21.927383image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:21.963961image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23611
90.1%
1 2597
 
9.9%

Most occurring characters

ValueCountFrequency (%)
0 23611
90.1%
1 2597
 
9.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23611
90.1%
1 2597
 
9.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23611
90.1%
1 2597
 
9.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23611
90.1%
1 2597
 
9.9%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26162 
1
 
46

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26162
99.8%
1 46
 
0.2%

Length

2025-05-15T14:09:22.010378image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:22.046215image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26162
99.8%
1 46
 
0.2%

Most occurring characters

ValueCountFrequency (%)
0 26162
99.8%
1 46
 
0.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26162
99.8%
1 46
 
0.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26162
99.8%
1 46
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26162
99.8%
1 46
 
0.2%

HourCounters Average AmbientOk Avg. [h]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26042 
1
 
166

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26042
99.4%
1 166
 
0.6%

Length

2025-05-15T14:09:22.088695image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:22.126684image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26042
99.4%
1 166
 
0.6%

Most occurring characters

ValueCountFrequency (%)
0 26042
99.4%
1 166
 
0.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26042
99.4%
1 166
 
0.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26042
99.4%
1 166
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26042
99.4%
1 166
 
0.6%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24494 
1
 
1714

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24494
93.5%
1 1714
 
6.5%

Length

2025-05-15T14:09:22.169565image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:22.205404image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24494
93.5%
1 1714
 
6.5%

Most occurring characters

ValueCountFrequency (%)
0 24494
93.5%
1 1714
 
6.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24494
93.5%
1 1714
 
6.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24494
93.5%
1 1714
 
6.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24494
93.5%
1 1714
 
6.5%

HourCounters Average AlarmActive Avg. [h]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26040 
1
 
168

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26040
99.4%
1 168
 
0.6%

Length

2025-05-15T14:09:22.252044image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:22.288612image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26040
99.4%
1 168
 
0.6%

Most occurring characters

ValueCountFrequency (%)
0 26040
99.4%
1 168
 
0.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26040
99.4%
1 168
 
0.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26040
99.4%
1 168
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26040
99.4%
1 168
 
0.6%

Total hour counter [h]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:09:22.332113image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:22.367562image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Grid on hours [h]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:09:22.407367image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:22.441045image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Grid ok hours [h]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:09:22.482621image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:22.516225image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Turbine ok hours [h]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:09:22.557604image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:22.593129image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Run hours [h]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:09:22.632879image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:22.666382image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Generator 1 hours [h]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:09:22.707856image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:22.741710image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Generator 2 hours [h]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:09:22.781209image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:22.817080image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Yaw hours [h]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:09:22.857343image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:22.891164image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Service hours [h]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:09:22.932982image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:22.966618image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Ambient ok hours [h]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:09:23.006341image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:23.041881image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Wind ok hours [h]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:09:23.082085image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:23.115847image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Production LatestAverage Active Power Gen 0 Avg. [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24706 
1
 
1502

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24706
94.3%
1 1502
 
5.7%

Length

2025-05-15T14:09:23.158033image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:23.194211image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24706
94.3%
1 1502
 
5.7%

Most occurring characters

ValueCountFrequency (%)
0 24706
94.3%
1 1502
 
5.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24706
94.3%
1 1502
 
5.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24706
94.3%
1 1502
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24706
94.3%
1 1502
 
5.7%

Production LatestAverage Active Power Gen 1 Avg. [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25730 
1
 
478

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25730
98.2%
1 478
 
1.8%

Length

2025-05-15T14:09:23.237022image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:23.274862image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25730
98.2%
1 478
 
1.8%

Most occurring characters

ValueCountFrequency (%)
0 25730
98.2%
1 478
 
1.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25730
98.2%
1 478
 
1.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25730
98.2%
1 478
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25730
98.2%
1 478
 
1.8%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25270 
1
 
938

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25270
96.4%
1 938
 
3.6%

Length

2025-05-15T14:09:23.317900image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:23.353926image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25270
96.4%
1 938
 
3.6%

Most occurring characters

ValueCountFrequency (%)
0 25270
96.4%
1 938
 
3.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25270
96.4%
1 938
 
3.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25270
96.4%
1 938
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25270
96.4%
1 938
 
3.6%

Production LatestAverage Total Active Power Avg. [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25236 
1
 
972

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25236
96.3%
1 972
 
3.7%

Length

2025-05-15T14:09:23.398371image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:23.434526image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25236
96.3%
1 972
 
3.7%

Most occurring characters

ValueCountFrequency (%)
0 25236
96.3%
1 972
 
3.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25236
96.3%
1 972
 
3.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25236
96.3%
1 972
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25236
96.3%
1 972
 
3.7%

Production LatestAverage Reactive Power Gen 0 Avg. [var]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24562 
1
 
1646

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24562
93.7%
1 1646
 
6.3%

Length

2025-05-15T14:09:23.477263image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:23.515092image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24562
93.7%
1 1646
 
6.3%

Most occurring characters

ValueCountFrequency (%)
0 24562
93.7%
1 1646
 
6.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24562
93.7%
1 1646
 
6.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24562
93.7%
1 1646
 
6.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24562
93.7%
1 1646
 
6.3%

Production LatestAverage Reactive Power Gen 1 Avg. [var]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24356 
1
 
1852

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24356
92.9%
1 1852
 
7.1%

Length

2025-05-15T14:09:23.558509image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:23.594566image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24356
92.9%
1 1852
 
7.1%

Most occurring characters

ValueCountFrequency (%)
0 24356
92.9%
1 1852
 
7.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24356
92.9%
1 1852
 
7.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24356
92.9%
1 1852
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24356
92.9%
1 1852
 
7.1%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24198 
1
 
2010

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24198
92.3%
1 2010
 
7.7%

Length

2025-05-15T14:09:23.639265image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:23.675443image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24198
92.3%
1 2010
 
7.7%

Most occurring characters

ValueCountFrequency (%)
0 24198
92.3%
1 2010
 
7.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24198
92.3%
1 2010
 
7.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24198
92.3%
1 2010
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24198
92.3%
1 2010
 
7.7%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
22693 
1
3515 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 22693
86.6%
1 3515
 
13.4%

Length

2025-05-15T14:09:23.718499image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:23.757205image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 22693
86.6%
1 3515
 
13.4%

Most occurring characters

ValueCountFrequency (%)
0 22693
86.6%
1 3515
 
13.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 22693
86.6%
1 3515
 
13.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 22693
86.6%
1 3515
 
13.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 22693
86.6%
1 3515
 
13.4%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:09:23.802243image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:23.836218image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:09:23.878206image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:23.912233image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26207 
1
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26207
> 99.9%
1 1
 
< 0.1%

Length

2025-05-15T14:09:23.952079image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:23.990268image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26207
> 99.9%
1 1
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 26207
> 99.9%
1 1
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26207
> 99.9%
1 1
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26207
> 99.9%
1 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26207
> 99.9%
1 1
 
< 0.1%

Total Active power [W]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26205 
1
 
3

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26205
> 99.9%
1 3
 
< 0.1%

Length

2025-05-15T14:09:24.033391image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:24.069680image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26205
> 99.9%
1 3
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 26205
> 99.9%
1 3
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26205
> 99.9%
1 3
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26205
> 99.9%
1 3
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26205
> 99.9%
1 3
 
< 0.1%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26094 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26094
99.6%
1 114
 
0.4%

Length

2025-05-15T14:09:24.114388image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:24.150618image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26094
99.6%
1 114
 
0.4%

Most occurring characters

ValueCountFrequency (%)
0 26094
99.6%
1 114
 
0.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26094
99.6%
1 114
 
0.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26094
99.6%
1 114
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26094
99.6%
1 114
 
0.4%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:09:24.194121image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:24.229535image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-15T14:09:24.427625image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:24.461379image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Total reactive power [var]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26031 
1
 
177

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26031
99.3%
1 177
 
0.7%

Length

2025-05-15T14:09:24.502276image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-15T14:09:24.538343image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26031
99.3%
1 177
 
0.7%

Most occurring characters

ValueCountFrequency (%)
0 26031
99.3%
1 177
 
0.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26031
99.3%
1 177
 
0.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26031
99.3%
1 177
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26031
99.3%
1 177
 
0.7%

Correlations

2025-05-15T14:09:24.665911image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Active power generator 2, Total accumulated [W]Active power limit [W]Active power limit sourceAmbient Temp. Avg. [°C]Ambient WindDir Absolute Avg. [°]Ambient WindDir Relative Avg. [°]Ambient WindSpeed Avg. [m/s]Ambient WindSpeed Max. [m/s]Ambient WindSpeed Min. [m/s]Ambient WindSpeed StdDev [m/s]Blades PitchAngle Avg. [°]Blades PitchAngle Max. [°]Blades PitchAngle Min. [°]Blades PitchAngle StdDev [°]Controller Ground Temp. Avg. [°C]Controller Hub Temp. Avg. [°C]Controller Top Temp. Avg. [°C]Controller VCP ChokecoilTemp. Avg. [°C]Controller VCP Temp. Avg. [°C]Controller VCP WaterTemp. Avg. [°C]Gear Bearing TemperatureHSGeneratorEnd Avg. [°C]Gear Bearing TemperatureHSMiddle Avg. [°C]Gear Bearing TemperatureHSRotorEnd Avg. [°C]Gear Bearing TemperatureHollowShaftGenerator Avg. [°C]Gear Bearing TemperatureHollowShaftRotor Avg. [°C]Gear Oil TemperatureBasis Avg. [°C]Gear Oil TemperatureLevel1 Avg. [°C]Generator Bearing Temp. Avg. [°C]Generator Bearing2 Temp. Avg. [°C]Generator CoolingWater Temp. Avg. [°C]Generator Phase1 Temp. Avg. [°C]Generator Phase2 Temp. Avg. [°C]Generator Phase3 Temp. Avg. [°C]Generator RPM Avg. [RPM]Generator RPM Max. [RPM]Generator RPM Min. [RPM]Generator RPM StdDev [RPM]Generator SlipRing Temp. Avg. [°C]Grid Busbar Temp. Avg. [°C]Grid InverterPhase1 Temp. Avg. [°C]Grid Production CosPhi Avg.Grid Production CurrentPhase1 Avg. [A]Grid Production CurrentPhase2 Avg. [A]Grid Production CurrentPhase3 Avg. [A]Grid Production Frequency Avg. [Hz]Grid Production PossiblePower Avg. [W]Grid Production PossiblePower Max. [W]Grid Production PossiblePower Min. [W]Grid Production PossiblePower StdDev [W]Grid Production Power Avg. [W]Grid Production Power Max. [W]Grid Production Power Min. [W]Grid Production Power StdDev [W]Grid Production ReactivePower Avg. [W]Grid Production ReactivePower Max. [W]Grid Production ReactivePower Min. [W]Grid Production ReactivePower StdDev [W]Grid Production VoltagePhase1 Avg. [V]Grid Production VoltagePhase2 Avg. [V]Grid Production VoltagePhase3 Avg. [V]Grid RotorInvPhase1 Temp. Avg. [°C]Grid RotorInvPhase2 Temp. Avg. [°C]Grid RotorInvPhase3 Temp. Avg. [°C]HVTrafo AirOutlet Temp. Avg. [°C]HVTrafo Phase1 Temp. Avg. [°C]HVTrafo Phase2 Temp. Avg. [°C]HVTrafo Phase3 Temp. Avg. [°C]HourCounters Average AlarmActive Avg. [h]HourCounters Average AmbientOk Avg. [h]HourCounters Average Gen1 Avg. [h]HourCounters Average Gen2 Avg. [h]HourCounters Average GridOk Avg. [h]HourCounters Average GridOn Avg. [h]HourCounters Average Run Avg. [h]HourCounters Average ServiceOn Avg. [h]HourCounters Average TurbineOk Avg. [h]HourCounters Average WindOk Avg. [h]HourCounters Average Yaw Avg. [h]Hydraulic Oil Temp. Avg. [°C]Nacelle Temp. Avg. [°C]Power factor set pointPower factor set point sourceProduction LatestAverage Active Power Gen 0 Avg. [W]Production LatestAverage Active Power Gen 1 Avg. [W]Production LatestAverage Active Power Gen 2 Avg. [W]Production LatestAverage Reactive Power Gen 0 Avg. [var]Production LatestAverage Reactive Power Gen 1 Avg. [var]Production LatestAverage Reactive Power Gen 2 Avg. [var]Production LatestAverage Total Active Power Avg. [W]Production LatestAverage Total Reactive Power Avg. [var]Reactive power generator 0,Total accumulated [var]Rotor RPM Avg. [RPM]Rotor RPM Max. [RPM]Rotor RPM Min. [RPM]Rotor RPM StdDev [RPM]Spinner Temp. Avg. [°C]Total Active power [W]Total reactive power [var]
Active power generator 2, Total accumulated [W]1.0000.0000.0000.0000.0000.0160.0000.0000.0000.0000.0000.0060.0000.0000.0000.0030.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0170.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.000
Active power limit [W]0.0001.0000.1350.0240.0000.0130.0000.0050.1130.0300.0260.0080.0290.0230.1070.0000.0000.0110.0060.0170.0100.0160.0060.0120.0080.0200.0220.0520.0000.0150.0410.0530.0530.0090.0000.0260.0370.0100.0000.0000.0230.0490.0540.0430.0000.0110.0380.0460.0220.0530.0790.0680.0690.0240.0270.0300.0080.0000.0090.0070.0000.0080.0090.0000.0080.0000.0130.2530.2540.0570.0250.3270.4230.2040.1590.2750.0950.0110.0080.0110.1350.1350.0560.0340.0190.0520.0160.0280.0580.0090.0000.0520.0000.0280.0330.0290.0000.006
Active power limit source0.0000.1351.0000.0100.0000.0000.0000.0000.0600.0070.0070.0140.0340.0020.0550.0000.0000.0000.0000.0000.0000.0000.0000.0040.0060.0000.0000.0000.0000.0050.0070.0000.0040.0000.0000.0150.0120.0000.0000.0040.0090.0240.0240.0250.0130.0000.2040.0000.0000.0240.0130.0300.0290.0050.0130.0080.0000.0000.0000.0000.0070.0080.0080.0000.0000.0000.0000.0730.1560.0370.0080.1710.3290.1100.1250.1840.0490.0060.0080.0040.9910.9910.0100.0200.0000.0080.0000.0100.0310.0000.0000.0000.0000.0200.0000.0150.0000.000
Ambient Temp. Avg. [°C]0.0000.0240.0101.0000.0140.0150.0130.0050.0170.0120.0110.0190.0110.0220.0080.0030.0160.0060.0140.0110.0100.0090.0100.0050.0200.0080.0050.0000.0000.0160.0020.0000.0000.0120.0130.0090.0170.0000.0000.0050.0190.0100.0130.0170.0040.0120.0140.0120.0190.0050.0060.0070.0090.0150.0060.0030.0000.0000.0000.0000.0090.0000.0000.0050.0000.0000.0000.0250.0200.0060.0150.0120.0180.0100.0040.0000.0100.0110.0000.0360.0100.0100.0130.0000.0090.0090.0060.0080.0000.0110.0100.0070.0120.0110.0070.0220.0000.013
Ambient WindDir Absolute Avg. [°]0.0000.0000.0000.0141.0000.1580.0140.0170.0090.0220.0260.0270.0230.0190.0000.0050.0130.0000.0000.0110.0000.0000.0000.0120.0070.0000.0370.0000.0000.0000.0000.0070.0000.0330.0400.0270.0190.0000.0030.0060.0150.0050.0180.0080.0000.0230.0070.0000.0090.0170.0000.0080.0000.0330.0070.0210.0240.0060.0000.0000.0080.0080.0140.0000.0060.0000.0000.0000.0000.0120.0370.0000.0000.0000.0000.0000.0000.0240.0000.0080.0000.0000.0330.0060.0130.0400.0000.0190.0120.0250.0000.0310.0400.0130.0140.0070.0000.000
Ambient WindDir Relative Avg. [°]0.0160.0130.0000.0150.1581.0000.0000.0140.0000.0000.0640.1220.0250.0280.0080.0090.0000.0100.0000.0000.0000.0080.0000.0260.0230.0000.0890.0000.0060.0000.0000.0000.0020.0560.1150.0450.0390.0020.0000.0000.0430.0110.0000.0060.0000.0070.0030.0100.0000.0090.0030.0110.0200.0530.0130.0210.0040.0000.0000.0090.0000.0000.0120.0200.0260.0000.0000.0400.0230.0000.0490.0100.0000.0210.0000.0130.0180.0200.0120.0000.0000.0000.0600.0000.0130.0740.0230.0280.0120.0280.0000.0530.0920.0360.0460.0120.0000.035
Ambient WindSpeed Avg. [m/s]0.0000.0000.0000.0130.0140.0001.0000.1010.1150.0120.0970.0340.0470.0370.0000.0000.0000.0100.0040.0220.0710.0700.0960.0760.0540.0360.0000.0000.0120.0070.0120.0080.0110.1180.0620.0590.0610.0190.0000.0490.0210.1950.1860.1890.0030.2350.1010.0910.0540.1850.0790.0740.0460.0210.0340.0330.0230.0000.0030.0000.0350.0330.0420.0020.0000.0000.0000.0000.0000.0150.0390.0060.0110.0000.0000.0000.0420.0080.0000.0190.0000.0000.0250.0970.0990.0170.0000.0000.1810.0110.0000.1150.0560.0600.0460.0010.0000.000
Ambient WindSpeed Max. [m/s]0.0000.0050.0000.0050.0170.0140.1011.0000.0330.0590.0630.0290.0280.0200.0000.0000.0000.0000.0000.0040.0370.0220.0150.0230.0190.0100.0000.0040.0080.0000.0150.0170.0180.0480.0550.0190.0350.0130.0030.0300.0230.0780.0870.0790.0000.0940.1470.0220.0910.0860.0820.0380.0570.0220.0420.0310.0270.0050.0020.0060.0340.0230.0190.0000.0000.0000.0000.0000.0120.0220.0340.0150.0120.0000.0000.0110.0440.0080.0000.0000.0000.0000.0180.0490.0470.0110.0030.0000.0720.0130.0000.0440.0470.0230.0220.0050.0000.000
Ambient WindSpeed Min. [m/s]0.0000.1130.0600.0170.0090.0000.1150.0331.0000.0370.0850.0350.1290.1010.0510.0000.0000.0000.0000.0040.0280.0280.0430.0430.0390.0080.0150.0000.0000.0120.0020.0000.0120.0930.0550.1150.0810.0100.0000.0290.0640.0880.0920.0830.0000.0840.0600.1360.0550.0870.0430.0960.0580.0850.0780.0620.0840.0000.0000.0040.0140.0070.0260.0120.0000.0000.0000.0850.0890.0590.0600.1160.1430.0590.0480.1030.0800.0070.0010.0120.0600.0600.0690.0580.0500.0610.0200.0300.0790.0540.0060.0720.0390.1020.0600.0110.0000.000
Ambient WindSpeed StdDev [m/s]0.0000.0300.0070.0120.0220.0000.0120.0590.0371.0000.0450.0000.0320.0870.0200.0080.0000.0050.0030.0030.0300.0220.0180.0040.0220.0180.0100.0000.0000.0000.0340.0360.0340.0350.0380.0090.0880.0000.0000.0380.0280.0320.0390.0330.0000.0300.0410.0260.1420.0370.0380.0110.1190.0460.0540.0390.0500.0000.0000.0000.0370.0220.0210.0220.0070.0000.0130.0300.0350.0100.0200.0420.0450.0340.0000.0470.0300.0570.0110.0000.0070.0070.0320.0080.0240.0260.0000.0330.0360.0160.0000.0240.0360.0080.0670.0000.0000.000
Blades PitchAngle Avg. [°]0.0000.0260.0070.0110.0260.0640.0970.0630.0850.0451.0000.3230.4350.4560.0240.0000.0050.0090.0270.0110.0350.0610.0190.1240.1520.0160.0530.0150.0140.0200.0240.0270.0160.2600.2180.2400.2400.0400.0140.0390.2570.1860.1900.2090.0070.2050.1930.1910.2530.2220.1670.1440.2360.3800.2560.2060.2640.0000.0000.0000.0410.0370.0440.0300.0340.0300.0280.1400.1090.1390.3900.0680.0670.1500.0480.0830.0990.0970.0060.0340.0070.0070.3380.0980.2410.3340.0860.2330.2240.2930.0400.2490.1970.2020.2030.0170.0000.039
Blades PitchAngle Max. [°]0.0060.0080.0140.0190.0270.1220.0340.0290.0350.0000.3231.0000.1690.1400.0090.0210.0000.0170.0000.0000.0320.0360.0280.0720.0780.0280.1060.0000.0100.0000.0070.0000.0000.1390.2710.0960.1030.0190.0050.0130.2240.1320.1320.1420.0000.1610.1710.1260.1790.1470.1410.0910.1400.2170.1630.0860.1200.0000.0000.0150.0000.0100.0000.0210.0110.0060.0000.0890.0680.0140.2230.0290.0420.0790.0490.0430.1620.0490.0160.0000.0140.0140.2460.0060.1370.2740.0400.0990.1510.1550.0000.1190.2320.0860.0970.0150.0000.023
Blades PitchAngle Min. [°]0.0000.0290.0340.0110.0230.0250.0470.0280.1290.0320.4350.1691.0000.5390.0210.0000.0130.0000.0260.0080.0430.0580.0280.1300.1450.0310.0190.0080.0000.0190.0250.0120.0120.2270.1440.3370.2520.0340.0090.0260.3380.1360.1330.1540.0000.1570.1480.1690.2000.1780.1330.1220.2130.5700.4130.3340.4360.0000.0000.0000.0240.0190.0190.0230.0210.0150.0260.1300.1000.2760.5350.0730.0650.1430.0240.0950.1320.0660.0000.0220.0340.0340.4060.1710.2730.3820.1730.4060.1780.4240.0580.2070.1210.2900.1920.0130.0150.070
Blades PitchAngle StdDev [°]0.0000.0230.0020.0220.0190.0280.0370.0200.1010.0870.4560.1400.5391.0000.0190.0000.0150.0140.0260.0230.0190.0370.0000.0860.1120.0190.0430.0000.0140.0270.0140.0090.0000.1990.1550.2480.4050.0310.0210.0280.2830.1330.1330.1450.0000.1770.1720.2440.2460.1610.1240.1430.2310.4600.3250.2650.4680.0040.0040.0000.0280.0270.0230.0250.0270.0300.0330.1280.1150.2220.4370.0940.0960.1250.0490.0850.0880.1490.0000.0210.0020.0020.3160.1370.2670.3150.1620.4710.1670.3460.0830.1740.1210.2100.3250.0060.0000.093
Controller Ground Temp. Avg. [°C]0.0000.1070.0550.0080.0000.0080.0000.0000.0510.0200.0240.0090.0210.0191.0000.0070.0000.0000.0000.0150.0000.0000.0020.0000.0000.0000.0130.0070.0000.0080.0070.0000.0000.0080.0000.0200.0150.0090.0000.0000.0000.0270.0230.0120.0000.0100.0180.0000.0230.0200.0000.0060.0310.0200.0080.0100.0150.0130.0030.0050.0000.0160.0110.0040.0000.0180.0000.1220.1190.0380.0170.1630.1880.0850.0430.1430.0430.0160.0000.0000.0550.0550.0210.0370.0180.0270.0110.0140.0140.0080.0070.0050.0000.0120.0130.0070.0000.000
Controller Hub Temp. Avg. [°C]0.0030.0000.0000.0030.0050.0090.0000.0000.0000.0080.0000.0210.0000.0000.0071.0000.0440.0220.0280.0190.0120.0150.0040.0090.0120.0110.0000.0000.0080.0280.0190.0230.0100.0120.0100.0000.0000.0000.0110.0140.0000.0040.0100.0060.0000.0000.0000.0060.0000.0000.0000.0000.0000.0000.0120.0100.0000.0000.0000.0000.0190.0000.0150.0180.0050.0040.0200.0260.0240.0090.0000.0230.0200.0140.0000.0150.0000.0000.0180.0230.0000.0000.0000.0250.0090.0000.0050.0090.0070.0090.0180.0080.0090.0000.0000.1010.0000.013
Controller Top Temp. Avg. [°C]0.0000.0000.0000.0160.0130.0000.0000.0000.0000.0000.0050.0000.0130.0150.0000.0441.0000.0000.0430.0010.0000.0000.0000.0070.0000.0070.0050.0030.0260.0080.0000.0000.0030.0110.0000.0080.0000.0000.0210.0000.0000.0000.0090.0050.0000.0000.0060.0040.0020.0060.0000.0070.0000.0140.0140.0060.0130.0110.0050.0040.0130.0030.0150.0000.0250.0000.0130.0100.0000.0270.0130.0090.0000.0030.0000.0030.0080.0000.0140.0310.0000.0000.0060.0380.0010.0060.0220.0130.0010.0230.0000.0000.0090.0000.0070.0220.0000.008
Controller VCP ChokecoilTemp. Avg. [°C]0.0000.0110.0000.0060.0000.0100.0100.0000.0000.0050.0090.0170.0000.0140.0000.0220.0001.0000.0460.0390.0680.0630.0140.0340.0500.0460.0190.0620.0680.0400.0770.0590.0770.0050.0040.0000.0210.0260.0190.0580.0210.0180.0160.0140.0000.0000.0130.0110.0000.0090.0190.0150.0080.0070.0120.0170.0050.0000.0000.0000.0580.0490.0400.0290.0280.0040.0490.0030.0100.0250.0000.0090.0000.0060.0000.0080.0000.0000.0170.0310.0000.0000.0240.0200.0000.0250.0320.0030.0130.0130.0090.0090.0100.0050.0230.0040.0000.004
Controller VCP Temp. Avg. [°C]0.0000.0060.0000.0140.0000.0000.0040.0000.0000.0030.0270.0000.0260.0260.0000.0280.0430.0461.0000.0320.0000.0140.0170.0220.0200.0280.0110.0190.0200.0300.0270.0310.0420.0000.0000.0130.0070.0320.0530.0340.0000.0000.0000.0000.0070.0080.0000.0000.0100.0000.0040.0000.0000.0000.0150.0130.0050.0000.0050.0000.0230.0250.0220.0280.0330.0090.0230.0020.0030.0270.0180.0110.0070.0090.0000.0150.0000.0090.0000.0480.0000.0000.0000.0370.0180.0000.0230.0170.0050.0110.0080.0000.0000.0180.0000.0370.0150.010
Controller VCP WaterTemp. Avg. [°C]0.0000.0170.0000.0110.0110.0000.0220.0040.0040.0030.0110.0000.0080.0230.0150.0190.0010.0390.0321.0000.0460.0520.0360.0510.0440.0380.0000.0480.0310.2910.0790.0830.0880.0220.0120.0020.0180.0260.0280.2140.0090.0090.0150.0000.0000.0100.0020.0000.0000.0000.0000.0000.0160.0180.0210.0320.0080.0100.0130.0130.2610.2930.2590.0060.0000.0130.0280.0000.0000.0000.0200.0000.0060.0000.0040.0000.0120.0150.0290.0110.0000.0000.0150.0000.0040.0170.0000.0140.0000.0210.0040.0120.0170.0220.0150.0190.0120.000
Gear Bearing TemperatureHSGeneratorEnd Avg. [°C]0.0000.0100.0000.0100.0000.0000.0710.0370.0280.0300.0350.0320.0430.0190.0000.0120.0000.0680.0000.0461.0000.3160.2080.2340.1290.2080.0270.0530.0870.0360.1120.1120.0870.1070.0640.0610.0760.0360.0050.0650.0480.0510.0540.0490.0000.0460.0520.0250.0330.0570.0530.0210.0300.0320.0430.0600.0430.0000.0000.0000.0510.0490.0580.0190.0040.0070.0000.0320.0350.0000.0340.0000.0000.0460.0000.0000.0320.0310.0630.0040.0000.0000.0390.0330.0080.0390.0140.0000.0460.0160.0020.0760.0690.0750.0720.0070.0000.000
Gear Bearing TemperatureHSMiddle Avg. [°C]0.0000.0160.0000.0090.0000.0080.0700.0220.0280.0220.0610.0360.0580.0370.0000.0150.0000.0630.0140.0520.3161.0000.1260.3000.1920.2460.0150.0630.1080.0430.1110.1090.1170.1490.0870.0730.1020.0230.0290.0610.0480.0360.0380.0330.0000.0340.0490.0250.0240.0340.0360.0000.0000.0400.0510.0670.0440.0040.0000.0000.0490.0560.0530.0180.0100.0000.0100.0150.0200.0000.0440.0080.0070.0260.0040.0070.0040.0310.0520.0080.0000.0000.0530.0370.0000.0520.0200.0160.0320.0270.0110.1260.0780.1040.0960.0000.0000.018
Gear Bearing TemperatureHSRotorEnd Avg. [°C]0.0000.0060.0000.0100.0000.0000.0960.0150.0430.0180.0190.0280.0280.0000.0020.0040.0000.0140.0170.0360.2080.1261.0000.1520.0990.1650.0500.0360.0160.0220.0630.0510.0480.1260.0400.0670.0690.0230.0210.0390.0150.0600.0700.0750.0000.0650.0640.0230.0350.0680.0510.0230.0240.0100.0250.0430.0290.0000.0000.0000.0370.0300.0320.0070.0070.0130.0000.0530.0590.0320.0060.0180.0150.0730.0000.0240.0190.0190.0490.0200.0000.0000.0100.0500.0320.0120.0100.0210.0610.0110.0000.0970.0720.0650.0610.0110.0000.007
Gear Bearing TemperatureHollowShaftGenerator Avg. [°C]0.0000.0120.0040.0050.0120.0260.0760.0230.0430.0040.1240.0720.1300.0860.0000.0090.0070.0340.0220.0510.2340.3000.1521.0000.3040.2020.0480.0670.1140.0540.0890.0930.0840.2040.0810.1750.1240.0390.0320.0390.1160.0510.0580.0560.0130.0570.0670.0410.0490.0560.0590.0210.0360.1120.0920.1170.1010.0000.0000.0000.0440.0570.0510.0300.0390.0140.0110.0310.0240.0080.1340.0000.0000.0430.0000.0100.0150.0260.0420.0170.0040.0040.1340.0440.0190.1400.0000.0690.0550.1010.0180.1920.0910.1770.1100.0290.0000.037
Gear Bearing TemperatureHollowShaftRotor Avg. [°C]0.0000.0080.0060.0200.0070.0230.0540.0190.0390.0220.1520.0780.1450.1120.0000.0120.0000.0500.0200.0440.1290.1920.0990.3041.0000.1180.0510.0560.0900.0450.0700.0680.0720.2230.1310.1810.1240.0290.0100.0460.1010.0310.0350.0360.0180.0510.0510.0440.0700.0420.0320.0070.0450.1300.1000.1100.0860.0000.0000.0000.0510.0440.0440.0270.0130.0000.0080.0260.0270.0600.1690.0000.0000.0400.0000.0060.0180.0320.0060.0210.0060.0060.1280.0480.0510.1380.0200.0860.0400.1170.0110.2060.1170.1830.1040.0140.0000.032
Gear Oil TemperatureBasis Avg. [°C]0.0000.0200.0000.0080.0000.0000.0360.0100.0080.0180.0160.0280.0310.0190.0000.0110.0070.0460.0280.0380.2080.2460.1650.2020.1181.0000.0370.0610.0590.0450.0820.0760.0830.1290.0740.0650.0850.0240.0000.0420.0260.0130.0170.0120.0000.0270.0280.0220.0170.0120.0120.0080.0000.0130.0330.0380.0400.0000.0000.0000.0390.0450.0410.0320.0000.0000.0000.0060.0030.0140.0270.0140.0130.0000.0070.0130.0130.0210.0530.0170.0000.0000.0260.0080.0000.0250.0060.0200.0120.0090.0180.1000.0760.0830.0840.0100.0000.015
Gear Oil TemperatureLevel1 Avg. [°C]0.0000.0220.0000.0050.0370.0890.0000.0000.0150.0100.0530.1060.0190.0430.0130.0000.0050.0190.0110.0000.0270.0150.0500.0480.0510.0371.0000.0000.0000.0310.0090.0130.0070.0690.1170.0370.0700.0140.0090.0130.0500.0220.0270.0340.0000.0280.0500.0400.0380.0340.0290.0310.0220.0500.0190.0000.0330.0000.0060.0000.0090.0170.0210.0020.0000.0000.0000.0540.0500.0090.0440.0350.0360.0580.0000.0430.0000.0220.0000.0090.0000.0000.0580.0000.0200.0860.0250.0500.0300.0260.0000.0610.0900.0300.0780.0230.0000.010
Generator Bearing Temp. Avg. [°C]0.0000.0520.0000.0000.0000.0000.0000.0040.0000.0000.0150.0000.0080.0000.0070.0000.0030.0620.0190.0480.0530.0630.0360.0670.0560.0610.0001.0000.1480.0470.0840.1050.0940.0280.0000.0390.0080.0210.0150.0200.0110.0060.0000.0000.0130.0000.0090.0000.0050.0000.0000.0080.0000.0000.0260.0290.0000.0000.0130.0000.0290.0440.0320.0090.0410.0230.0420.0000.0030.0050.0200.0090.0000.0000.0000.0080.0000.0000.0230.0230.0000.0000.0140.0060.0000.0050.0000.0000.0100.0040.0060.0380.0000.0390.0140.0000.0000.008
Generator Bearing2 Temp. Avg. [°C]0.0000.0000.0000.0000.0000.0060.0120.0080.0000.0000.0140.0100.0000.0140.0000.0080.0260.0680.0200.0310.0870.1080.0160.1140.0900.0590.0000.1481.0000.0400.1030.1180.0940.0290.0000.0180.0130.0040.0110.0160.0000.0130.0150.0130.0000.0120.0000.0130.0000.0200.0000.0220.0040.0000.0260.0240.0000.0000.0000.0000.0220.0270.0340.0120.0520.0330.0370.0000.0000.0080.0110.0000.0000.0000.0000.0000.0000.0000.0000.0210.0000.0000.0000.0000.0060.0000.0000.0000.0160.0000.0040.0390.0000.0210.0000.0240.0000.000
Generator CoolingWater Temp. Avg. [°C]0.0000.0150.0050.0160.0000.0000.0070.0000.0120.0000.0200.0000.0190.0270.0080.0280.0080.0400.0300.2910.0360.0430.0220.0540.0450.0450.0310.0470.0401.0000.0780.0680.0700.0330.0310.0290.0240.0290.0000.1330.0300.0120.0190.0120.0000.0120.0030.0000.0010.0000.0000.0000.0030.0250.0300.0310.0170.0000.0000.0080.1900.2190.2090.0060.0120.0130.0320.0000.0000.0000.0390.0030.0000.0000.0080.0000.0180.0210.0160.0100.0050.0050.0260.0000.0140.0300.0000.0320.0000.0230.0120.0270.0270.0400.0180.0050.0000.006
Generator Phase1 Temp. Avg. [°C]0.0000.0410.0070.0020.0000.0000.0120.0150.0020.0340.0240.0070.0250.0140.0070.0190.0000.0770.0270.0790.1120.1110.0630.0890.0700.0820.0090.0840.1030.0781.0000.5770.5290.0390.0390.0210.0290.0060.0020.1180.0210.0240.0400.0400.0000.0250.0320.0000.0080.0310.0400.0160.0000.0180.0390.0470.0000.0070.0130.0060.1150.1020.1250.0000.0160.0070.0300.0000.0040.0000.0240.0000.0000.0050.0000.0000.0100.0080.0090.0130.0070.0070.0130.0000.0170.0240.0300.0000.0230.0000.0100.0400.0310.0460.0120.0000.0000.014
Generator Phase2 Temp. Avg. [°C]0.0000.0530.0000.0000.0070.0000.0080.0170.0000.0360.0270.0000.0120.0090.0000.0230.0000.0590.0310.0830.1120.1090.0510.0930.0680.0760.0130.1050.1180.0680.5771.0000.4950.0470.0310.0160.0250.0150.0000.1060.0210.0240.0400.0380.0000.0300.0260.0000.0210.0340.0460.0200.0120.0130.0330.0380.0000.0000.0000.0070.1060.0950.1140.0100.0280.0140.0330.0000.0160.0000.0130.0000.0000.0000.0000.0000.0000.0140.0000.0050.0000.0000.0070.0000.0170.0190.0270.0000.0230.0000.0050.0460.0270.0430.0130.0040.0000.013
Generator Phase3 Temp. Avg. [°C]0.0000.0530.0040.0000.0000.0020.0110.0180.0120.0340.0160.0000.0120.0000.0000.0100.0030.0770.0420.0880.0870.1170.0480.0840.0720.0830.0070.0940.0940.0700.5290.4951.0000.0390.0220.0110.0290.0000.0090.1010.0180.0310.0440.0390.0130.0450.0400.0190.0300.0430.0530.0310.0170.0040.0220.0360.0030.0000.0140.0070.1080.0860.1110.0120.0180.0280.0200.0000.0120.0020.0120.0000.0000.0000.0000.0000.0110.0140.0000.0070.0040.0040.0040.0000.0140.0160.0370.0030.0300.0070.0080.0370.0120.0410.0150.0000.0000.012
Generator RPM Avg. [RPM]0.0000.0090.0000.0120.0330.0560.1180.0480.0930.0350.2600.1390.2270.1990.0080.0120.0110.0050.0000.0220.1070.1490.1260.2040.2230.1290.0690.0280.0290.0330.0390.0470.0391.0000.4020.3770.4870.0360.0000.0080.1810.1430.1470.1390.0000.1490.1590.1090.1700.1460.1190.0720.1470.2190.1620.1940.1880.0000.0000.0000.0260.0380.0190.0200.0080.0000.0000.0980.0920.0530.2490.0570.0480.1120.0140.0610.0320.0740.0120.0180.0000.0000.2730.0580.1020.2740.0140.1220.1540.1770.0570.6880.3650.3610.4000.0080.0000.065
Generator RPM Max. [RPM]0.0000.0000.0000.0130.0400.1150.0620.0550.0550.0380.2180.2710.1440.1550.0000.0100.0000.0040.0000.0120.0640.0870.0400.0810.1310.0740.1170.0000.0000.0310.0390.0310.0220.4021.0000.1470.3350.0280.0040.0220.1430.1240.1270.1230.0000.1300.1520.1190.1660.1230.1410.0780.1260.2010.1530.0880.1180.0000.0150.0040.0310.0310.0250.0320.0050.0000.0000.0650.0600.0690.2200.0240.0100.0710.0270.0360.0230.0650.0000.0000.0000.0000.1910.0000.1680.2200.0090.1310.1290.1450.0000.3050.7160.1370.2430.0120.0000.009
Generator RPM Min. [RPM]0.0000.0260.0150.0090.0270.0450.0590.0190.1150.0090.2400.0960.3370.2480.0200.0000.0080.0000.0130.0020.0610.0730.0670.1750.1810.0650.0370.0390.0180.0290.0210.0160.0110.3770.1471.0000.2830.0290.0030.0030.2350.0930.1040.1170.0020.1230.0860.1560.0870.1250.0760.1150.0910.2850.2320.2840.2430.0060.0000.0000.0170.0220.0190.0300.0300.0240.0230.0780.0670.1470.3740.0450.0410.0880.0010.0510.1120.0540.0060.0140.0150.0150.3330.1480.1150.3060.0220.2220.1280.2160.0670.3830.1290.7380.2490.0000.0000.071
Generator RPM StdDev [RPM]0.0000.0370.0120.0170.0190.0390.0610.0350.0810.0880.2400.1030.2520.4050.0150.0000.0000.0210.0070.0180.0760.1020.0690.1240.1240.0850.0700.0080.0130.0240.0290.0250.0290.4870.3350.2831.0000.0270.0050.0160.2500.1450.1500.1400.0010.1500.1760.2070.2170.1490.1300.1490.2030.2400.1770.1840.3170.0000.0020.0000.0220.0230.0200.0110.0000.0000.0140.1140.1220.0320.2530.1010.0900.1230.0340.0840.0470.1320.0000.0050.0120.0120.2740.0250.1440.2840.0050.2760.1570.1720.0740.4010.2850.2570.6710.0000.0000.087
Generator SlipRing Temp. Avg. [°C]0.0000.0100.0000.0000.0000.0020.0190.0130.0100.0000.0400.0190.0340.0310.0090.0000.0000.0260.0320.0260.0360.0230.0230.0390.0290.0240.0140.0210.0040.0290.0060.0150.0000.0360.0280.0290.0271.0000.0210.0290.0230.0120.0090.0150.0000.0140.0220.0230.0270.0070.0000.0090.0080.0260.0160.0160.0300.0100.0050.0050.0050.0140.0200.0630.0190.0000.0130.0090.0160.0000.0380.0090.0030.0110.0000.0000.0000.0180.0050.0570.0000.0000.0260.0000.0140.0280.0000.0120.0100.0230.0000.0290.0300.0250.0230.0000.0000.000
Grid Busbar Temp. Avg. [°C]0.0000.0000.0000.0000.0030.0000.0000.0030.0000.0000.0140.0050.0090.0210.0000.0110.0210.0190.0530.0280.0050.0290.0210.0320.0100.0000.0090.0150.0110.0000.0020.0000.0090.0000.0040.0030.0050.0211.0000.0070.0020.0000.0000.0000.0000.0130.0040.0070.0050.0000.0000.0000.0000.0030.0000.0000.0230.0000.0090.0000.0000.0040.0060.0290.0390.0460.0770.0000.0000.0220.0140.0050.0000.0000.0000.0090.0180.0120.0130.0350.0000.0000.0010.0260.0000.0000.0210.0120.0000.0240.0000.0000.0000.0000.0000.0000.0000.000
Grid InverterPhase1 Temp. Avg. [°C]0.0000.0000.0040.0050.0060.0000.0490.0300.0290.0380.0390.0130.0260.0280.0000.0140.0000.0580.0340.2140.0650.0610.0390.0390.0460.0420.0130.0200.0160.1330.1180.1060.1010.0080.0220.0030.0160.0290.0071.0000.0130.0600.0740.0560.0000.0510.0330.0310.0340.0560.0360.0350.0190.0180.0260.0320.0140.0000.0000.0000.2180.2130.2350.0220.0000.0070.0000.0110.0070.0000.0110.0000.0000.0230.0000.0030.0030.0180.0200.0110.0040.0040.0140.0060.0240.0150.0120.0000.0470.0040.0030.0070.0140.0180.0000.0080.0000.014
Grid Production CosPhi Avg.0.0000.0230.0090.0190.0150.0430.0210.0230.0640.0280.2570.2240.3380.2830.0000.0000.0000.0210.0000.0090.0480.0480.0150.1160.1010.0260.0500.0110.0000.0300.0210.0210.0180.1810.1430.2350.2500.0230.0020.0131.0000.2350.1760.2040.0000.1760.1860.2020.1890.2630.1940.1910.2420.4240.2760.2280.3210.0000.0000.0000.0170.0210.0170.0150.0200.0150.0080.0790.0610.0110.4570.0310.0270.0630.0340.0500.1770.0820.0140.0050.0090.0090.5580.0040.1850.4850.0560.3380.2750.2920.0540.1740.1180.1890.2070.0040.0000.096
Grid Production CurrentPhase1 Avg. [A]0.0000.0490.0240.0100.0050.0110.1950.0780.0880.0320.1860.1320.1360.1330.0270.0040.0000.0180.0000.0090.0510.0360.0600.0510.0310.0130.0220.0060.0130.0120.0240.0240.0310.1430.1240.0930.1450.0120.0000.0600.2351.0000.7210.6620.0050.4840.2690.2490.2470.6740.3050.3640.3810.2190.1350.1310.1580.0000.0150.0100.0410.0320.0350.0000.0000.0000.0000.1320.1000.0530.1540.0530.0700.1330.0650.0680.1580.1030.0000.0170.0240.0240.3200.1450.3490.2520.0130.0750.6550.1500.0000.1350.0940.0730.1080.0000.0000.000
Grid Production CurrentPhase2 Avg. [A]0.0000.0540.0240.0130.0180.0000.1860.0870.0920.0390.1900.1320.1330.1330.0230.0100.0090.0160.0000.0150.0540.0380.0700.0580.0350.0170.0270.0000.0150.0190.0400.0400.0440.1470.1270.1040.1500.0090.0000.0740.1760.7211.0000.6920.0000.5030.2800.2470.2560.6030.3050.3230.3190.2270.1460.1350.1650.0030.0110.0050.0510.0390.0520.0120.0000.0000.0000.1280.1100.0560.1650.0530.0650.1330.0560.0650.1510.1050.0000.0210.0240.0240.2460.1490.3640.2530.0120.0800.5710.1510.0000.1390.0990.0860.1180.0050.0000.007
Grid Production CurrentPhase3 Avg. [A]0.0000.0430.0250.0170.0080.0060.1890.0790.0830.0330.2090.1420.1540.1450.0120.0060.0050.0140.0000.0000.0490.0330.0750.0560.0360.0120.0340.0000.0130.0120.0400.0380.0390.1390.1230.1170.1400.0150.0000.0560.2040.6620.6921.0000.0000.5200.2900.2660.2710.6350.3310.3160.3470.2170.1550.1320.1570.0000.0000.0000.0320.0280.0460.0140.0100.0000.0000.1280.1070.0560.1810.0520.0670.1320.0540.0640.1270.0940.0000.0210.0250.0250.2700.1510.3790.2450.0100.0890.6010.1460.0000.1460.0960.0900.1240.0110.0000.000
Grid Production Frequency Avg. [Hz]0.0000.0000.0130.0040.0000.0000.0030.0000.0000.0000.0070.0000.0000.0000.0000.0000.0000.0000.0070.0000.0000.0000.0000.0130.0180.0000.0000.0130.0000.0000.0000.0000.0130.0000.0000.0020.0010.0000.0000.0000.0000.0050.0000.0001.0000.0000.0000.0020.0000.0000.0000.0120.0000.0000.0000.0000.0050.0490.0460.0440.0000.0000.0050.0000.0000.0000.0140.0000.0000.0000.0050.0520.0000.0000.0000.0000.0000.0000.0000.0090.0130.0130.0000.0000.0100.0000.0000.0010.0000.0000.0000.0000.0080.0000.0000.0000.0000.000
Grid Production PossiblePower Avg. [W]0.0170.0110.0000.0120.0230.0070.2350.0940.0840.0300.2050.1610.1570.1770.0100.0000.0000.0000.0080.0100.0460.0340.0650.0570.0510.0270.0280.0000.0120.0120.0250.0300.0450.1490.1300.1230.1500.0140.0130.0510.1760.4840.5030.5200.0001.0000.3840.3860.4110.5590.2900.2700.3030.1530.1440.0890.1360.0000.0000.0000.0360.0300.0430.0050.0000.0000.0070.0290.0540.0270.2250.0320.0320.0310.0040.0280.1280.1070.0000.0290.0000.0000.1830.1590.4450.1680.0000.1240.5320.1060.0070.1490.1120.1010.1270.0000.0000.011
Grid Production PossiblePower Max. [W]0.0000.0380.2040.0140.0070.0030.1010.1470.0600.0410.1930.1710.1480.1720.0180.0000.0060.0130.0000.0020.0520.0490.0640.0670.0510.0280.0500.0090.0000.0030.0320.0260.0400.1590.1520.0860.1760.0220.0040.0330.1860.2690.2800.2900.0000.3841.0000.2750.3830.2940.5340.1800.2820.1720.1480.0760.1590.0000.0000.0000.0190.0100.0110.0000.0000.0060.0000.0750.0860.0420.2090.0810.0840.0740.0290.0680.0610.0900.0350.0140.2040.2040.1720.0670.2890.1810.0000.1250.2990.1170.0050.1470.1150.0780.1600.0050.0000.003
Grid Production PossiblePower Min. [W]0.0000.0460.0000.0120.0000.0100.0910.0220.1360.0260.1910.1260.1690.2440.0000.0060.0040.0110.0000.0000.0250.0250.0230.0410.0440.0220.0400.0000.0130.0000.0000.0000.0190.1090.1190.1560.2070.0230.0070.0310.2020.2490.2470.2660.0020.3860.2751.0000.3040.2860.2410.4060.2610.1600.1290.0790.1910.0000.0000.0000.0150.0190.0250.0000.0000.0000.0150.0320.0450.0540.2230.0140.0030.0260.0100.0140.0950.0930.0000.0270.0000.0000.1620.0910.2870.1650.0000.2120.2920.1120.0280.1190.1000.1280.1780.0000.0000.000
Grid Production PossiblePower StdDev [W]0.0000.0220.0000.0190.0090.0000.0540.0910.0550.1420.2530.1790.2000.2460.0230.0000.0020.0000.0100.0000.0330.0240.0350.0490.0700.0170.0380.0050.0000.0010.0080.0210.0300.1700.1660.0870.2170.0270.0050.0340.1890.2470.2560.2710.0000.4110.3830.3041.0000.2810.2780.1800.6000.2220.1950.1020.1820.0000.0000.0000.0160.0120.0180.0130.0000.0000.0070.0540.0760.0430.2560.0520.0470.0560.0070.0400.0610.1220.0000.0330.0000.0000.1880.0480.3240.2100.0440.1500.2840.1740.0000.1530.1460.0700.1950.0160.0000.002
Grid Production Power Avg. [W]0.0000.0530.0240.0050.0170.0090.1850.0860.0870.0370.2220.1470.1780.1610.0200.0000.0060.0090.0000.0000.0570.0340.0680.0560.0420.0120.0340.0000.0200.0000.0310.0340.0430.1460.1230.1250.1490.0070.0000.0560.2630.6740.6030.6350.0000.5590.2940.2860.2811.0000.3570.3860.4140.2300.1490.1430.1620.0000.0000.0000.0430.0250.0420.0000.0010.0000.0080.1310.1120.0530.1950.0540.0660.1360.0530.0670.1390.1080.0000.0240.0240.0240.3820.1710.4260.2600.0100.1020.8110.1560.0000.1430.0990.1030.1310.0110.0030.000
Grid Production Power Max. [W]0.0000.0790.0130.0060.0000.0030.0790.0820.0430.0380.1670.1410.1330.1240.0000.0000.0000.0190.0040.0000.0530.0360.0510.0590.0320.0120.0290.0000.0000.0000.0400.0460.0530.1190.1410.0760.1300.0000.0000.0360.1940.3050.3050.3310.0000.2900.5340.2410.2780.3571.0000.2220.2940.1730.1590.0740.1220.0000.0000.0000.0330.0190.0190.0150.0000.0000.0060.0910.0670.0080.1720.0150.0200.0750.0340.0390.0520.0680.0210.0140.0130.0130.1870.0430.2600.1970.0280.0790.3310.1070.0000.1490.1110.0580.1380.0080.0000.000
Grid Production Power Min. [W]0.0000.0680.0300.0070.0080.0110.0740.0380.0960.0110.1440.0910.1220.1430.0060.0000.0070.0150.0000.0000.0210.0000.0230.0210.0070.0080.0310.0080.0220.0000.0160.0200.0310.0720.0780.1150.1490.0090.0000.0350.1910.3640.3230.3160.0120.2700.1800.4060.1800.3860.2221.0000.2990.1390.0990.1460.1400.0060.0140.0000.0270.0160.0200.0040.0000.0060.0090.0430.0280.0350.1380.0190.0220.0380.0400.0200.0940.0940.0110.0250.0300.0300.2070.0770.2400.1560.0210.1310.3770.0860.0000.0750.0570.0900.1290.0050.0000.000
Grid Production Power StdDev [W]0.0000.0690.0290.0090.0000.0200.0460.0570.0580.1190.2360.1400.2130.2310.0310.0000.0000.0080.0000.0160.0300.0000.0240.0360.0450.0000.0220.0000.0040.0030.0000.0120.0170.1470.1260.0910.2030.0080.0000.0190.2420.3810.3190.3470.0000.3030.2820.2610.6000.4140.2940.2991.0000.2480.1740.1270.2120.0000.0060.0000.0000.0000.0000.0000.0010.0000.0220.1190.1020.0780.2160.0850.0910.1210.0650.0900.0830.0970.0000.0180.0290.0290.2910.0770.2900.2280.0560.1310.4300.1810.0000.1370.1090.0590.1750.0160.0000.000
Grid Production ReactivePower Avg. [W]0.0000.0240.0050.0150.0330.0530.0210.0220.0850.0460.3800.2170.5700.4600.0200.0000.0140.0070.0000.0180.0320.0400.0100.1120.1300.0130.0500.0000.0000.0250.0180.0130.0040.2190.2010.2850.2400.0260.0030.0180.4240.2190.2270.2170.0000.1530.1720.1600.2220.2300.1730.1390.2481.0000.5260.4060.5630.0020.0000.0000.0190.0240.0120.0190.0250.0270.0210.1350.1140.2780.6120.0670.0690.1260.0170.0770.1360.1110.0070.0180.0050.0050.5620.1540.2680.6620.1690.4750.2160.6460.0450.2050.1640.2330.1990.0100.0000.095
Grid Production ReactivePower Max. [W]0.0000.0270.0130.0060.0070.0130.0340.0420.0780.0540.2560.1630.4130.3250.0080.0120.0140.0120.0150.0210.0430.0510.0250.0920.1000.0330.0190.0260.0260.0300.0390.0330.0220.1620.1530.2320.1770.0160.0000.0260.2760.1350.1460.1550.0000.1440.1480.1290.1950.1490.1590.0990.1740.5261.0000.3410.4270.0000.0000.0000.0320.0330.0250.0290.0330.0210.0270.0890.0810.2450.4440.0590.0600.0840.0130.0620.1340.1370.0000.0060.0130.0130.3330.1740.2190.3410.1410.3110.1440.3770.0110.1430.1240.2130.1320.0120.0000.034
Grid Production ReactivePower Min. [W]0.0000.0300.0080.0030.0210.0210.0330.0310.0620.0390.2060.0860.3340.2650.0100.0100.0060.0170.0130.0320.0600.0670.0430.1170.1100.0380.0000.0290.0240.0310.0470.0380.0360.1940.0880.2840.1840.0160.0000.0320.2280.1310.1350.1320.0000.0890.0760.0790.1020.1430.0740.1460.1270.4060.3411.0000.3620.0100.0000.0120.0380.0390.0290.0140.0260.0290.0320.0920.0810.2070.3630.0530.0550.0730.0200.0540.1180.1360.0050.0080.0080.0080.3180.1710.1350.3150.0910.2670.1390.3110.0380.1900.0790.2710.1500.0020.0000.057
Grid Production ReactivePower StdDev [W]0.0000.0080.0000.0000.0240.0040.0230.0270.0840.0500.2640.1200.4360.4680.0150.0000.0130.0050.0050.0080.0430.0440.0290.1010.0860.0400.0330.0000.0000.0170.0000.0000.0030.1880.1180.2430.3170.0300.0230.0140.3210.1580.1650.1570.0050.1360.1590.1910.1820.1620.1220.1400.2120.5630.4270.3621.0000.0000.0000.0000.0000.0100.0000.0240.0090.0160.0310.0950.0950.2730.4850.0680.0670.0890.0220.0610.0910.1610.0280.0120.0000.0000.3780.2020.2160.3920.1990.4590.1570.4460.0480.1570.1120.2040.2820.0000.0000.077
Grid Production VoltagePhase1 Avg. [V]0.0000.0000.0000.0000.0060.0000.0000.0050.0000.0000.0000.0000.0000.0040.0130.0000.0110.0000.0000.0100.0000.0040.0000.0000.0000.0000.0000.0000.0000.0000.0070.0000.0000.0000.0000.0060.0000.0100.0000.0000.0000.0000.0030.0000.0490.0000.0000.0000.0000.0000.0000.0060.0000.0020.0000.0100.0001.0000.5950.5960.0000.0000.0110.0000.0000.0000.0050.0000.0000.0000.0040.0480.0130.0000.0000.0000.0000.0040.0010.0070.0000.0000.0030.0000.0000.0000.0130.0000.0000.0040.0000.0000.0100.0050.0000.0080.0000.000
Grid Production VoltagePhase2 Avg. [V]0.0000.0090.0000.0000.0000.0000.0030.0020.0000.0000.0000.0000.0000.0040.0030.0000.0050.0000.0050.0130.0000.0000.0000.0000.0000.0000.0060.0130.0000.0000.0130.0000.0140.0000.0150.0000.0020.0050.0090.0000.0000.0150.0110.0000.0460.0000.0000.0000.0000.0000.0000.0140.0060.0000.0000.0000.0000.5951.0000.6290.0000.0040.0080.0030.0000.0060.0140.0000.0000.0000.0050.0450.0120.0000.0000.0000.0000.0000.0130.0000.0000.0000.0000.0000.0000.0000.0000.0050.0000.0020.0000.0000.0170.0000.0000.0000.0000.000
Grid Production VoltagePhase3 Avg. [V]0.0000.0070.0000.0000.0000.0090.0000.0060.0040.0000.0000.0150.0000.0000.0050.0000.0040.0000.0000.0130.0000.0000.0000.0000.0000.0000.0000.0000.0000.0080.0060.0070.0070.0000.0040.0000.0000.0050.0000.0000.0000.0100.0050.0000.0440.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0120.0000.5960.6291.0000.0030.0060.0140.0080.0000.0000.0060.0050.0110.0000.0070.0490.0160.0100.0000.0070.0050.0090.0080.0110.0000.0000.0000.0000.0000.0000.0030.0000.0000.0000.0000.0000.0080.0000.0000.0000.0000.000
Grid RotorInvPhase1 Temp. Avg. [°C]0.0000.0000.0070.0090.0080.0000.0350.0340.0140.0370.0410.0000.0240.0280.0000.0190.0130.0580.0230.2610.0510.0490.0370.0440.0510.0390.0090.0290.0220.1900.1150.1060.1080.0260.0310.0170.0220.0050.0000.2180.0170.0410.0510.0320.0000.0360.0190.0150.0160.0430.0330.0270.0000.0190.0320.0380.0000.0000.0000.0031.0000.4610.4120.0080.0060.0030.0070.0200.0150.0000.0190.0000.0050.0320.0000.0110.0170.0280.0110.0120.0070.0070.0180.0090.0170.0260.0210.0000.0360.0000.0080.0290.0300.0380.0170.0000.0150.008
Grid RotorInvPhase2 Temp. Avg. [°C]0.0000.0080.0080.0000.0080.0000.0330.0230.0070.0220.0370.0100.0190.0270.0160.0000.0030.0490.0250.2930.0490.0560.0300.0570.0440.0450.0170.0440.0270.2190.1020.0950.0860.0380.0310.0220.0230.0140.0040.2130.0210.0320.0390.0280.0000.0300.0100.0190.0120.0250.0190.0160.0000.0240.0330.0390.0100.0000.0040.0060.4611.0000.2940.0110.0050.0000.0120.0000.0000.0110.0170.0080.0020.0090.0000.0000.0160.0210.0210.0000.0080.0080.0190.0000.0090.0210.0220.0070.0220.0110.0070.0320.0260.0390.0140.0020.0140.010
Grid RotorInvPhase3 Temp. Avg. [°C]0.0000.0090.0080.0000.0140.0120.0420.0190.0260.0210.0440.0000.0190.0230.0110.0150.0150.0400.0220.2590.0580.0530.0320.0510.0440.0410.0210.0320.0340.2090.1250.1140.1110.0190.0250.0190.0200.0200.0060.2350.0170.0350.0520.0460.0050.0430.0110.0250.0180.0420.0190.0200.0000.0120.0250.0290.0000.0110.0080.0140.4120.2941.0000.0000.0000.0110.0000.0000.0000.0040.0200.0100.0050.0000.0000.0050.0080.0200.0000.0090.0080.0080.0150.0000.0250.0120.0200.0000.0320.0000.0000.0260.0280.0430.0150.0080.0000.020
HVTrafo AirOutlet Temp. Avg. [°C]0.0000.0000.0000.0050.0000.0200.0020.0000.0120.0220.0300.0210.0230.0250.0040.0180.0000.0290.0280.0060.0190.0180.0070.0300.0270.0320.0020.0090.0120.0060.0000.0100.0120.0200.0320.0300.0110.0630.0290.0220.0150.0000.0120.0140.0000.0050.0000.0000.0130.0000.0150.0040.0000.0190.0290.0140.0240.0000.0030.0080.0080.0110.0001.0000.0290.0150.0260.0000.0000.0070.0240.0000.0000.0000.0000.0000.0000.0110.0080.0290.0000.0000.0000.0150.0090.0190.0060.0130.0040.0190.0000.0180.0160.0240.0250.0000.0000.000
HVTrafo Phase1 Temp. Avg. [°C]0.0000.0080.0000.0000.0060.0260.0000.0000.0000.0070.0340.0110.0210.0270.0000.0050.0250.0280.0330.0000.0040.0100.0070.0390.0130.0000.0000.0410.0520.0120.0160.0280.0180.0080.0050.0300.0000.0190.0390.0000.0200.0000.0000.0100.0000.0000.0000.0000.0000.0010.0000.0000.0010.0250.0330.0260.0090.0000.0000.0000.0060.0050.0000.0291.0000.1670.2040.0000.0000.0560.0380.0060.0000.0000.0000.0000.0250.0000.0000.0020.0000.0000.0140.0590.0000.0120.0080.0250.0000.0190.0000.0130.0000.0260.0000.0090.0000.000
HVTrafo Phase2 Temp. Avg. [°C]0.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0300.0060.0150.0300.0180.0040.0000.0040.0090.0130.0070.0000.0130.0140.0000.0000.0000.0230.0330.0130.0070.0140.0280.0000.0000.0240.0000.0000.0460.0070.0150.0000.0000.0000.0000.0000.0060.0000.0000.0000.0000.0060.0000.0270.0210.0290.0160.0000.0060.0000.0030.0000.0110.0150.1671.0000.1980.0000.0090.0520.0390.0050.0000.0000.0000.0040.0060.0100.0060.0060.0000.0000.0200.0520.0000.0220.0130.0230.0000.0240.0090.0030.0000.0110.0000.0000.0000.000
HVTrafo Phase3 Temp. Avg. [°C]0.0000.0130.0000.0000.0000.0000.0000.0000.0000.0130.0280.0000.0260.0330.0000.0200.0130.0490.0230.0280.0000.0100.0000.0110.0080.0000.0000.0420.0370.0320.0300.0330.0200.0000.0000.0230.0140.0130.0770.0000.0080.0000.0000.0000.0140.0070.0000.0150.0070.0080.0060.0090.0220.0210.0270.0320.0310.0050.0140.0060.0070.0120.0000.0260.2040.1981.0000.0110.0080.0440.0430.0000.0110.0070.0000.0020.0090.0170.0000.0170.0000.0000.0200.0550.0000.0180.0000.0290.0060.0180.0080.0000.0000.0260.0140.0160.0000.000
HourCounters Average AlarmActive Avg. [h]0.0000.2530.0730.0250.0000.0400.0000.0000.0850.0300.1400.0890.1300.1280.1220.0260.0100.0030.0020.0000.0320.0150.0530.0310.0260.0060.0540.0000.0000.0000.0000.0000.0000.0980.0650.0780.1140.0090.0000.0110.0790.1320.1280.1280.0000.0290.0750.0320.0540.1310.0910.0430.1190.1350.0890.0920.0950.0000.0000.0050.0200.0000.0000.0000.0000.0000.0111.0000.5690.1760.0000.3830.4920.7390.3680.4520.1630.0210.0140.0000.0730.0730.1600.1230.0000.1570.0760.0000.1320.0990.0000.0890.0510.0680.0850.0230.0000.005
HourCounters Average AmbientOk Avg. [h]0.0000.2540.1560.0200.0000.0230.0000.0120.0890.0350.1090.0680.1000.1150.1190.0240.0000.0100.0030.0000.0350.0200.0590.0240.0270.0030.0500.0030.0000.0000.0040.0160.0120.0920.0600.0670.1220.0160.0000.0070.0610.1000.1100.1070.0000.0540.0860.0450.0760.1120.0670.0280.1020.1140.0810.0810.0950.0000.0000.0110.0150.0000.0000.0000.0000.0090.0080.5691.0000.1830.0000.6960.5660.6880.1860.6170.2020.0330.0210.0000.1560.1560.1160.1200.0020.1270.0760.0000.1080.0760.0000.0810.0520.0630.0950.0270.0000.000
HourCounters Average Gen1 Avg. [h]0.0000.0570.0370.0060.0120.0000.0150.0220.0590.0100.1390.0140.2760.2220.0380.0090.0270.0250.0270.0000.0000.0000.0320.0080.0600.0140.0090.0050.0080.0000.0000.0000.0020.0530.0690.1470.0320.0000.0220.0000.0110.0530.0560.0560.0000.0270.0420.0540.0430.0530.0080.0350.0780.2780.2450.2070.2730.0000.0000.0000.0000.0110.0040.0070.0560.0520.0440.1760.1831.0000.4940.1380.1240.2520.0120.1500.0280.0140.0150.0180.0370.0370.0250.6480.3360.0190.3200.1790.0660.2440.0060.0490.0490.1320.0100.0130.0000.006
HourCounters Average Gen2 Avg. [h]0.0000.0250.0080.0150.0370.0490.0390.0340.0600.0200.3900.2230.5350.4370.0170.0000.0130.0000.0180.0200.0340.0440.0060.1340.1690.0270.0440.0200.0110.0390.0240.0130.0120.2490.2200.3740.2530.0380.0140.0110.4570.1540.1650.1810.0050.2250.2090.2230.2560.1950.1720.1380.2160.6120.4440.3630.4850.0040.0050.0070.0190.0170.0200.0240.0380.0390.0430.0000.0000.4941.0000.0000.0000.0000.0000.0030.1330.0980.0000.0170.0080.0080.5670.3030.4980.5130.1230.4870.2110.4690.0450.2300.1810.3240.2050.0040.0000.086
HourCounters Average GridOk Avg. [h]0.0000.3270.1710.0120.0000.0100.0060.0150.1160.0420.0680.0290.0730.0940.1630.0230.0090.0090.0110.0000.0000.0080.0180.0000.0000.0140.0350.0090.0000.0030.0000.0000.0000.0570.0240.0450.1010.0090.0050.0000.0310.0530.0530.0520.0520.0320.0810.0140.0520.0540.0150.0190.0850.0670.0590.0530.0680.0480.0450.0490.0000.0080.0100.0000.0060.0050.0000.3830.6960.1380.0001.0000.7180.4840.2050.7840.1370.0000.0000.0000.1710.1710.0810.0790.0000.0790.0750.0000.0520.0440.0070.0480.0200.0440.0830.0310.0000.000
HourCounters Average GridOn Avg. [h]0.0000.4230.3290.0180.0000.0000.0110.0120.1430.0450.0670.0420.0650.0960.1880.0200.0000.0000.0070.0060.0000.0070.0150.0000.0000.0130.0360.0000.0000.0000.0000.0000.0000.0480.0100.0410.0900.0030.0000.0000.0270.0700.0650.0670.0000.0320.0840.0030.0470.0660.0200.0220.0910.0690.0600.0550.0670.0130.0120.0160.0050.0020.0050.0000.0000.0000.0110.4920.5660.1240.0000.7181.0000.3860.3270.6380.1950.0000.0000.0060.3290.3290.0960.0770.0000.0880.0650.0000.0800.0460.0060.0420.0110.0360.0730.0370.0000.000
HourCounters Average Run Avg. [h]0.0000.2040.1100.0100.0000.0210.0000.0000.0590.0340.1500.0790.1430.1250.0850.0140.0030.0060.0090.0000.0460.0260.0730.0430.0400.0000.0580.0000.0000.0000.0050.0000.0000.1120.0710.0880.1230.0110.0000.0230.0630.1330.1330.1320.0000.0310.0740.0260.0560.1360.0750.0380.1210.1260.0840.0730.0890.0000.0000.0100.0320.0090.0000.0000.0000.0000.0070.7390.6880.2520.0000.4840.3861.0000.1100.5670.1640.0240.0180.0000.1100.1100.1400.1550.0140.1420.0760.0090.1330.0930.0000.1040.0540.0800.0940.0270.0000.000
HourCounters Average ServiceOn Avg. [h]0.0000.1590.1250.0040.0000.0000.0000.0000.0480.0000.0480.0490.0240.0490.0430.0000.0000.0000.0000.0040.0000.0040.0000.0000.0000.0070.0000.0000.0000.0080.0000.0000.0000.0140.0270.0010.0340.0000.0000.0000.0340.0650.0560.0540.0000.0040.0290.0100.0070.0530.0340.0400.0650.0170.0130.0200.0220.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.3680.1860.0120.0000.2050.3270.1101.0000.2210.0570.0100.0000.0000.1250.1250.0500.0240.0000.0320.0180.0000.0710.0160.0000.0000.0250.0000.0190.0000.0000.000
HourCounters Average TurbineOk Avg. [h]0.0000.2750.1840.0000.0000.0130.0000.0110.1030.0470.0830.0430.0950.0850.1430.0150.0030.0080.0150.0000.0000.0070.0240.0100.0060.0130.0430.0080.0000.0000.0000.0000.0000.0610.0360.0510.0840.0000.0090.0030.0500.0680.0650.0640.0000.0280.0680.0140.0400.0670.0390.0200.0900.0770.0620.0540.0610.0000.0000.0070.0110.0000.0050.0000.0000.0040.0020.4520.6170.1500.0030.7840.6380.5670.2211.0000.1130.0000.0000.0000.1840.1840.0920.0760.0090.0870.0550.0000.0650.0550.0000.0540.0270.0460.0680.0300.0000.000
HourCounters Average WindOk Avg. [h]0.0000.0950.0490.0100.0000.0180.0420.0440.0800.0300.0990.1620.1320.0880.0430.0000.0080.0000.0000.0120.0320.0040.0190.0150.0180.0130.0000.0000.0000.0180.0100.0000.0110.0320.0230.1120.0470.0000.0180.0030.1770.1580.1510.1270.0000.1280.0610.0950.0610.1390.0520.0940.0830.1360.1340.1180.0910.0000.0000.0050.0170.0160.0080.0000.0250.0060.0090.1630.2020.0280.1330.1370.1950.1640.0570.1131.0000.0500.0140.0060.0490.0490.2000.0130.1210.1820.0390.1070.1350.0780.0100.0340.0130.1120.0300.0120.0000.011
HourCounters Average Yaw Avg. [h]0.0000.0110.0060.0110.0240.0200.0080.0080.0070.0570.0970.0490.0660.1490.0160.0000.0000.0000.0090.0150.0310.0310.0190.0260.0320.0210.0220.0000.0000.0210.0080.0140.0140.0740.0650.0540.1320.0180.0120.0180.0820.1030.1050.0940.0000.1070.0900.0930.1220.1080.0680.0940.0970.1110.1370.1360.1610.0040.0000.0090.0280.0210.0200.0110.0000.0100.0170.0210.0330.0140.0980.0000.0000.0240.0100.0000.0501.0000.0000.0000.0060.0060.1010.0170.1020.1210.0140.1060.1030.0990.0010.0630.0560.0570.1130.0000.0000.007
Hydraulic Oil Temp. Avg. [°C]0.0000.0080.0080.0000.0000.0120.0000.0000.0010.0110.0060.0160.0000.0000.0000.0180.0140.0170.0000.0290.0630.0520.0490.0420.0060.0530.0000.0230.0000.0160.0090.0000.0000.0120.0000.0060.0000.0050.0130.0200.0140.0000.0000.0000.0000.0000.0350.0000.0000.0000.0210.0110.0000.0070.0000.0050.0280.0010.0130.0080.0110.0210.0000.0080.0000.0060.0000.0140.0210.0150.0000.0000.0000.0180.0000.0000.0140.0001.0000.0060.0080.0080.0160.0320.0000.0120.0430.0060.0000.0140.0000.0000.0000.0140.0240.0000.0000.000
Nacelle Temp. Avg. [°C]0.0000.0110.0040.0360.0080.0000.0190.0000.0120.0000.0340.0000.0220.0210.0000.0230.0310.0310.0480.0110.0040.0080.0200.0170.0210.0170.0090.0230.0210.0100.0130.0050.0070.0180.0000.0140.0050.0570.0350.0110.0050.0170.0210.0210.0090.0290.0140.0270.0330.0240.0140.0250.0180.0180.0060.0080.0120.0070.0000.0110.0120.0000.0090.0290.0020.0060.0170.0000.0000.0180.0170.0000.0060.0000.0000.0000.0060.0000.0061.0000.0040.0040.0070.0220.0240.0110.0280.0020.0300.0240.0000.0150.0120.0110.0000.0240.0000.003
Power factor set point0.0000.1350.9910.0100.0000.0000.0000.0000.0600.0070.0070.0140.0340.0020.0550.0000.0000.0000.0000.0000.0000.0000.0000.0040.0060.0000.0000.0000.0000.0050.0070.0000.0040.0000.0000.0150.0120.0000.0000.0040.0090.0240.0240.0250.0130.0000.2040.0000.0000.0240.0130.0300.0290.0050.0130.0080.0000.0000.0000.0000.0070.0080.0080.0000.0000.0000.0000.0730.1560.0370.0080.1710.3290.1100.1250.1840.0490.0060.0080.0041.0000.9910.0100.0200.0000.0080.0000.0100.0310.0000.0000.0000.0000.0200.0000.0150.0000.000
Power factor set point source0.0000.1350.9910.0100.0000.0000.0000.0000.0600.0070.0070.0140.0340.0020.0550.0000.0000.0000.0000.0000.0000.0000.0000.0040.0060.0000.0000.0000.0000.0050.0070.0000.0040.0000.0000.0150.0120.0000.0000.0040.0090.0240.0240.0250.0130.0000.2040.0000.0000.0240.0130.0300.0290.0050.0130.0080.0000.0000.0000.0000.0070.0080.0080.0000.0000.0000.0000.0730.1560.0370.0080.1710.3290.1100.1250.1840.0490.0060.0080.0040.9911.0000.0100.0200.0000.0080.0000.0100.0310.0000.0000.0000.0000.0200.0000.0150.0000.000
Production LatestAverage Active Power Gen 0 Avg. [W]0.0000.0560.0100.0130.0330.0600.0250.0180.0690.0320.3380.2460.4060.3160.0210.0000.0060.0240.0000.0150.0390.0530.0100.1340.1280.0260.0580.0140.0000.0260.0130.0070.0040.2730.1910.3330.2740.0260.0010.0140.5580.3200.2460.2700.0000.1830.1720.1620.1880.3820.1870.2070.2910.5620.3330.3180.3780.0030.0000.0000.0180.0190.0150.0000.0140.0200.0200.1600.1160.0250.5670.0810.0960.1400.0500.0920.2000.1010.0160.0070.0100.0101.0000.0150.1830.6940.0290.3700.4760.4280.0740.2490.1600.2780.2280.0140.0000.113
Production LatestAverage Active Power Gen 1 Avg. [W]0.0000.0340.0200.0000.0060.0000.0970.0490.0580.0080.0980.0060.1710.1370.0370.0250.0380.0200.0370.0000.0330.0370.0500.0440.0480.0080.0000.0060.0000.0000.0000.0000.0000.0580.0000.1480.0250.0000.0260.0060.0040.1450.1490.1510.0000.1590.0670.0910.0480.1710.0430.0770.0770.1540.1740.1710.2020.0000.0000.0000.0090.0000.0000.0150.0590.0520.0550.1230.1200.6480.3030.0790.0770.1550.0240.0760.0130.0170.0320.0220.0200.0200.0151.0000.0380.0090.2600.0990.2210.1590.0030.0530.0000.1340.0180.0000.0000.000
Production LatestAverage Active Power Gen 2 Avg. [W]0.0000.0190.0000.0090.0130.0130.0990.0470.0500.0240.2410.1370.2730.2670.0180.0090.0010.0000.0180.0040.0080.0000.0320.0190.0510.0000.0200.0000.0060.0140.0170.0170.0140.1020.1680.1150.1440.0140.0000.0240.1850.3490.3640.3790.0100.4450.2890.2870.3240.4260.2600.2400.2900.2680.2190.1350.2160.0000.0000.0000.0170.0090.0250.0090.0000.0000.0000.0000.0020.3360.4980.0000.0000.0140.0000.0090.1210.1020.0000.0240.0000.0000.1830.0381.0000.1660.0770.2840.4690.1940.0090.0970.1300.1030.1060.0000.0040.010
Production LatestAverage Reactive Power Gen 0 Avg. [var]0.0000.0520.0080.0090.0400.0740.0170.0110.0610.0260.3340.2740.3820.3150.0270.0000.0060.0250.0000.0170.0390.0520.0120.1400.1380.0250.0860.0050.0000.0300.0240.0190.0160.2740.2200.3060.2840.0280.0000.0150.4850.2520.2530.2450.0000.1680.1810.1650.2100.2600.1970.1560.2280.6620.3410.3150.3920.0000.0000.0000.0260.0210.0120.0190.0120.0220.0180.1570.1270.0190.5130.0790.0880.1420.0320.0870.1820.1210.0120.0110.0080.0080.6940.0090.1661.0000.0340.3620.2550.5970.0580.2540.1900.2490.2360.0000.0000.118
Production LatestAverage Reactive Power Gen 1 Avg. [var]0.0000.0160.0000.0060.0000.0230.0000.0030.0200.0000.0860.0400.1730.1620.0110.0050.0220.0320.0230.0000.0140.0200.0100.0000.0200.0060.0250.0000.0000.0000.0300.0270.0370.0140.0090.0220.0050.0000.0210.0120.0560.0130.0120.0100.0000.0000.0000.0000.0440.0100.0280.0210.0560.1690.1410.0910.1990.0130.0000.0030.0210.0220.0200.0060.0080.0130.0000.0760.0760.3200.1230.0750.0650.0760.0180.0550.0390.0140.0430.0280.0000.0000.0290.2600.0770.0341.0000.0720.0000.6020.0130.0000.0150.0140.0000.0160.0000.019
Production LatestAverage Reactive Power Gen 2 Avg. [var]0.0000.0280.0100.0080.0190.0280.0000.0000.0300.0330.2330.0990.4060.4710.0140.0090.0130.0030.0170.0140.0000.0160.0210.0690.0860.0200.0500.0000.0000.0320.0000.0000.0030.1220.1310.2220.2760.0120.0120.0000.3380.0750.0800.0890.0010.1240.1250.2120.1500.1020.0790.1310.1310.4750.3110.2670.4590.0000.0050.0000.0000.0070.0000.0130.0250.0230.0290.0000.0000.1790.4870.0000.0000.0090.0000.0000.1070.1060.0060.0020.0100.0100.3700.0990.2840.3620.0721.0000.1170.4350.0890.1030.1000.1840.2210.0000.0000.117
Production LatestAverage Total Active Power Avg. [W]0.0000.0580.0310.0000.0120.0120.1810.0720.0790.0360.2240.1510.1780.1670.0140.0070.0010.0130.0050.0000.0460.0320.0610.0550.0400.0120.0300.0100.0160.0000.0230.0230.0300.1540.1290.1280.1570.0100.0000.0470.2750.6550.5710.6010.0000.5320.2990.2920.2840.8110.3310.3770.4300.2160.1440.1390.1570.0000.0000.0000.0360.0220.0320.0040.0000.0000.0060.1320.1080.0660.2110.0520.0800.1330.0710.0650.1350.1030.0000.0300.0310.0310.4760.2210.4690.2550.0000.1171.0000.1560.0000.1430.1010.1050.1240.0090.0040.000
Production LatestAverage Total Reactive Power Avg. [var]0.0000.0090.0000.0110.0250.0280.0110.0130.0540.0160.2930.1550.4240.3460.0080.0090.0230.0130.0110.0210.0160.0270.0110.1010.1170.0090.0260.0040.0000.0230.0000.0000.0070.1770.1450.2160.1720.0230.0240.0040.2920.1500.1510.1460.0000.1060.1170.1120.1740.1560.1070.0860.1810.6460.3770.3110.4460.0040.0020.0000.0000.0110.0000.0190.0190.0240.0180.0990.0760.2440.4690.0440.0460.0930.0160.0550.0780.0990.0140.0240.0000.0000.4280.1590.1940.5970.6020.4350.1561.0000.0300.1510.1430.1740.1350.0150.0000.065
Reactive power generator 0,Total accumulated [var]0.0000.0000.0000.0100.0000.0000.0000.0000.0060.0000.0400.0000.0580.0830.0070.0180.0000.0090.0080.0040.0020.0110.0000.0180.0110.0180.0000.0060.0040.0120.0100.0050.0080.0570.0000.0670.0740.0000.0000.0030.0540.0000.0000.0000.0000.0070.0050.0280.0000.0000.0000.0000.0000.0450.0110.0380.0480.0000.0000.0000.0080.0070.0000.0000.0000.0090.0080.0000.0000.0060.0450.0070.0060.0000.0000.0000.0100.0010.0000.0000.0000.0000.0740.0030.0090.0580.0130.0890.0000.0301.0000.0510.0000.0550.0580.0000.0000.302
Rotor RPM Avg. [RPM]0.0000.0520.0000.0070.0310.0530.1150.0440.0720.0240.2490.1190.2070.1740.0050.0080.0000.0090.0000.0120.0760.1260.0970.1920.2060.1000.0610.0380.0390.0270.0400.0460.0370.6880.3050.3830.4010.0290.0000.0070.1740.1350.1390.1460.0000.1490.1470.1190.1530.1430.1490.0750.1370.2050.1430.1900.1570.0000.0000.0000.0290.0320.0260.0180.0130.0030.0000.0890.0810.0490.2300.0480.0420.1040.0000.0540.0340.0630.0000.0150.0000.0000.2490.0530.0970.2540.0000.1030.1430.1510.0511.0000.2780.3670.3600.0160.0000.062
Rotor RPM Max. [RPM]0.0000.0000.0000.0120.0400.0920.0560.0470.0390.0360.1970.2320.1210.1210.0000.0090.0090.0100.0000.0170.0690.0780.0720.0910.1170.0760.0900.0000.0000.0270.0310.0270.0120.3650.7160.1290.2850.0300.0000.0140.1180.0940.0990.0960.0080.1120.1150.1000.1460.0990.1110.0570.1090.1640.1240.0790.1120.0100.0170.0080.0300.0260.0280.0160.0000.0000.0000.0510.0520.0490.1810.0200.0110.0540.0250.0270.0130.0560.0000.0120.0000.0000.1600.0000.1300.1900.0150.1000.1010.1430.0000.2781.0000.1280.1990.0070.0000.009
Rotor RPM Min. [RPM]0.0000.0280.0200.0110.0130.0360.0600.0230.1020.0080.2020.0860.2900.2100.0120.0000.0000.0050.0180.0220.0750.1040.0650.1770.1830.0830.0300.0390.0210.0400.0460.0430.0410.3610.1370.7380.2570.0250.0000.0180.1890.0730.0860.0900.0000.1010.0780.1280.0700.1030.0580.0900.0590.2330.2130.2710.2040.0050.0000.0000.0380.0390.0430.0240.0260.0110.0260.0680.0630.1320.3240.0440.0360.0800.0000.0460.1120.0570.0140.0110.0200.0200.2780.1340.1030.2490.0140.1840.1050.1740.0550.3670.1281.0000.2250.0000.0000.062
Rotor RPM StdDev [RPM]0.0000.0330.0000.0070.0140.0460.0460.0220.0600.0670.2030.0970.1920.3250.0130.0000.0070.0230.0000.0150.0720.0960.0610.1100.1040.0840.0780.0140.0000.0180.0120.0130.0150.4000.2430.2490.6710.0230.0000.0000.2070.1080.1180.1240.0000.1270.1600.1780.1950.1310.1380.1290.1750.1990.1320.1500.2820.0000.0000.0000.0170.0140.0150.0250.0000.0000.0140.0850.0950.0100.2050.0830.0730.0940.0190.0680.0300.1130.0240.0000.0000.0000.2280.0180.1060.2360.0000.2210.1240.1350.0580.3600.1990.2251.0000.0040.0000.071
Spinner Temp. Avg. [°C]0.0000.0290.0150.0220.0070.0120.0010.0050.0110.0000.0170.0150.0130.0060.0070.1010.0220.0040.0370.0190.0070.0000.0110.0290.0140.0100.0230.0000.0240.0050.0000.0040.0000.0080.0120.0000.0000.0000.0000.0080.0040.0000.0050.0110.0000.0000.0050.0000.0160.0110.0080.0050.0160.0100.0120.0020.0000.0080.0000.0000.0000.0020.0080.0000.0090.0000.0160.0230.0270.0130.0040.0310.0370.0270.0000.0300.0120.0000.0000.0240.0150.0150.0140.0000.0000.0000.0160.0000.0090.0150.0000.0160.0070.0000.0041.0000.0120.011
Total Active power [W]0.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0150.0000.0000.0000.0000.0000.0150.0120.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0030.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0150.0140.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0040.0000.0000.0000.0040.0000.0000.0000.0000.0000.0000.0121.0000.000
Total reactive power [var]0.0000.0060.0000.0130.0000.0350.0000.0000.0000.0000.0390.0230.0700.0930.0000.0130.0080.0040.0100.0000.0000.0180.0070.0370.0320.0150.0100.0080.0000.0060.0140.0130.0120.0650.0090.0710.0870.0000.0000.0140.0960.0000.0070.0000.0000.0110.0030.0000.0020.0000.0000.0000.0000.0950.0340.0570.0770.0000.0000.0000.0080.0100.0200.0000.0000.0000.0000.0050.0000.0060.0860.0000.0000.0000.0000.0000.0110.0070.0000.0030.0000.0000.1130.0000.0100.1180.0190.1170.0000.0650.3020.0620.0090.0620.0710.0110.0001.000

Missing values

2025-05-15T14:09:12.286526image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
A simple visualization of nullity by column.
2025-05-15T14:09:13.013488image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

TimestampGenerator RPM Max. [RPM]Generator RPM Min. [RPM]Generator RPM Avg. [RPM]Generator RPM StdDev [RPM]Generator Bearing Temp. Avg. [°C]Generator Phase1 Temp. Avg. [°C]Generator Phase2 Temp. Avg. [°C]Generator Phase3 Temp. Avg. [°C]Generator SlipRing Temp. Avg. [°C]Generator Bearing2 Temp. Avg. [°C]Generator CoolingWater Temp. Avg. [°C]Hydraulic Oil Temp. Avg. [°C]Gear Oil Temp. Avg. [°C]Gear Bearing Temp. Avg. [°C]Gear Oil TemperatureBasis Avg. [°C]Gear Oil TemperatureLevel1 Avg. [°C]Gear Oil TemperatureLevel2_3 Avg. [°C]Gear Bearing TemperatureHSRotorEnd Avg. [°C]Gear Bearing TemperatureHSGeneratorEnd Avg. [°C]Gear Bearing TemperatureHSMiddle Avg. [°C]Gear Bearing TemperatureHollowShaftRotor Avg. [°C]Gear Bearing TemperatureHollowShaftGenerator Avg. [°C]Nacelle Temp. Avg. [°C]Rotor RPM Max. [RPM]Rotor RPM Min. [RPM]Rotor RPM Avg. [RPM]Rotor RPM StdDev [RPM]Ambient WindSpeed Max. [m/s]Ambient WindSpeed Min. [m/s]Ambient WindSpeed Avg. [m/s]Ambient WindSpeed StdDev [m/s]Ambient WindDir Relative Avg. [°]Ambient WindDir Absolute Avg. [°]Ambient Temp. Avg. [°C]Ambient WindSpeed Estimated Avg. [m/s]Grid InverterPhase1 Temp. Avg. [°C]Grid RotorInvPhase1 Temp. Avg. [°C]Grid RotorInvPhase2 Temp. Avg. [°C]Grid RotorInvPhase3 Temp. Avg. [°C]Grid Production Power Avg. [W]Grid Production CosPhi Avg.Grid Production Frequency Avg. [Hz]Grid Production VoltagePhase1 Avg. [V]Grid Production VoltagePhase2 Avg. [V]Grid Production VoltagePhase3 Avg. [V]Grid Production CurrentPhase1 Avg. [A]Grid Production CurrentPhase2 Avg. [A]Grid Production CurrentPhase3 Avg. [A]Grid Production Power Max. [W]Grid Production Power Min. [W]Grid Busbar Temp. Avg. [°C]Grid Production Power StdDev [W]Grid Production ReactivePower Avg. [W]Grid Production ReactivePower Max. [W]Grid Production ReactivePower Min. [W]Grid Production ReactivePower StdDev [W]Grid Production PossiblePower Avg. [W]Grid Production PossiblePower Max. [W]Grid Production PossiblePower Min. [W]Grid Production PossiblePower StdDev [W]Grid Production PossibleInductive Avg. [var]Grid Production PossibleInductive Max. [var]Grid Production PossibleInductive Min. [var]Grid Production PossibleInductive StdDev [var]Grid Production PossibleCapacitive Avg. [var]Grid Production PossibleCapacitive Max. [var]Grid Production PossibleCapacitive Min. [var]Grid Production PossibleCapacitive StdDev [var]Active power limit [W]Active power limit sourceReactive power set point [var]Power factor set pointPower factor set point sourceController Ground Temp. Avg. [°C]Controller Top Temp. Avg. [°C]Controller Hub Temp. Avg. [°C]Controller VCP Temp. Avg. [°C]Controller VCP ChokecoilTemp. Avg. [°C]Controller VCP WaterTemp. Avg. [°C]Spinner Temp. Avg. [°C]Spinner Temp. SlipRing Avg. [°C]Blades PitchAngle Min. [°]Blades PitchAngle Max. [°]Blades PitchAngle Avg. [°]Blades PitchAngle StdDev [°]HVTrafo Phase1 Temp. Avg. [°C]HVTrafo Phase2 Temp. Avg. [°C]HVTrafo Phase3 Temp. Avg. [°C]HVTrafo AirOutlet Temp. Avg. [°C]HourCounters Average Total Avg. [h]HourCounters Average GridOn Avg. [h]HourCounters Average GridOk Avg. [h]HourCounters Average TurbineOk Avg. [h]HourCounters Average Run Avg. [h]HourCounters Average Gen1 Avg. [h]HourCounters Average Gen2 Avg. [h]HourCounters Average Yaw Avg. [h]HourCounters Average ServiceOn Avg. [h]HourCounters Average AmbientOk Avg. [h]HourCounters Average WindOk Avg. [h]HourCounters Average AlarmActive Avg. [h]Total hour counter [h]Grid on hours [h]Grid ok hours [h]Turbine ok hours [h]Run hours [h]Generator 1 hours [h]Generator 2 hours [h]Yaw hours [h]Service hours [h]Ambient ok hours [h]Wind ok hours [h]Production LatestAverage Active Power Gen 0 Avg. [W]Production LatestAverage Active Power Gen 1 Avg. [W]Production LatestAverage Active Power Gen 2 Avg. [W]Production LatestAverage Total Active Power Avg. [W]Production LatestAverage Reactive Power Gen 0 Avg. [var]Production LatestAverage Reactive Power Gen 1 Avg. [var]Production LatestAverage Reactive Power Gen 2 Avg. [var]Production LatestAverage Total Reactive Power Avg. [var]Active power generator 0, Total accumulated [W]Active power generator 1, Total accumulated [W]Active power generator 2, Total accumulated [W]Total Active power [W]Reactive power generator 0,Total accumulated [var]Reactive power generator 1, Total accumulated [var]Reactive power generator 2, Total accumulated [var]Total reactive power [var]
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32020-01-01 00:30:0000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000
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62020-01-01 01:00:0000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000
72020-01-01 01:10:0000000011000000100010000000100010000100000000000000000010000000000000000000010000000000000000000000000000000000000000000000000000
82020-01-01 01:20:0000000000000000000000000011100010000000000000000000000000000000000000000000010010000000000000000000000000000000000000000000000000
92020-01-01 01:30:0000100000000000000000000011000000000110000000000000000110000000000000000000000000000000000000000010000000000000000000000000000000
TimestampGenerator RPM Max. [RPM]Generator RPM Min. [RPM]Generator RPM Avg. [RPM]Generator RPM StdDev [RPM]Generator Bearing Temp. Avg. [°C]Generator Phase1 Temp. Avg. [°C]Generator Phase2 Temp. Avg. [°C]Generator Phase3 Temp. Avg. [°C]Generator SlipRing Temp. Avg. [°C]Generator Bearing2 Temp. Avg. [°C]Generator CoolingWater Temp. Avg. [°C]Hydraulic Oil Temp. Avg. [°C]Gear Oil Temp. Avg. [°C]Gear Bearing Temp. Avg. [°C]Gear Oil TemperatureBasis Avg. [°C]Gear Oil TemperatureLevel1 Avg. [°C]Gear Oil TemperatureLevel2_3 Avg. [°C]Gear Bearing TemperatureHSRotorEnd Avg. [°C]Gear Bearing TemperatureHSGeneratorEnd Avg. [°C]Gear Bearing TemperatureHSMiddle Avg. [°C]Gear Bearing TemperatureHollowShaftRotor Avg. [°C]Gear Bearing TemperatureHollowShaftGenerator Avg. [°C]Nacelle Temp. Avg. [°C]Rotor RPM Max. [RPM]Rotor RPM Min. [RPM]Rotor RPM Avg. [RPM]Rotor RPM StdDev [RPM]Ambient WindSpeed Max. [m/s]Ambient WindSpeed Min. [m/s]Ambient WindSpeed Avg. [m/s]Ambient WindSpeed StdDev [m/s]Ambient WindDir Relative Avg. [°]Ambient WindDir Absolute Avg. [°]Ambient Temp. Avg. [°C]Ambient WindSpeed Estimated Avg. [m/s]Grid InverterPhase1 Temp. Avg. [°C]Grid RotorInvPhase1 Temp. Avg. [°C]Grid RotorInvPhase2 Temp. Avg. [°C]Grid RotorInvPhase3 Temp. Avg. [°C]Grid Production Power Avg. [W]Grid Production CosPhi Avg.Grid Production Frequency Avg. [Hz]Grid Production VoltagePhase1 Avg. [V]Grid Production VoltagePhase2 Avg. [V]Grid Production VoltagePhase3 Avg. [V]Grid Production CurrentPhase1 Avg. [A]Grid Production CurrentPhase2 Avg. [A]Grid Production CurrentPhase3 Avg. [A]Grid Production Power Max. [W]Grid Production Power Min. [W]Grid Busbar Temp. Avg. [°C]Grid Production Power StdDev [W]Grid Production ReactivePower Avg. [W]Grid Production ReactivePower Max. [W]Grid Production ReactivePower Min. [W]Grid Production ReactivePower StdDev [W]Grid Production PossiblePower Avg. [W]Grid Production PossiblePower Max. [W]Grid Production PossiblePower Min. [W]Grid Production PossiblePower StdDev [W]Grid Production PossibleInductive Avg. [var]Grid Production PossibleInductive Max. [var]Grid Production PossibleInductive Min. [var]Grid Production PossibleInductive StdDev [var]Grid Production PossibleCapacitive Avg. [var]Grid Production PossibleCapacitive Max. [var]Grid Production PossibleCapacitive Min. [var]Grid Production PossibleCapacitive StdDev [var]Active power limit [W]Active power limit sourceReactive power set point [var]Power factor set pointPower factor set point sourceController Ground Temp. Avg. [°C]Controller Top Temp. Avg. [°C]Controller Hub Temp. Avg. [°C]Controller VCP Temp. Avg. [°C]Controller VCP ChokecoilTemp. Avg. [°C]Controller VCP WaterTemp. Avg. [°C]Spinner Temp. Avg. [°C]Spinner Temp. SlipRing Avg. [°C]Blades PitchAngle Min. [°]Blades PitchAngle Max. [°]Blades PitchAngle Avg. [°]Blades PitchAngle StdDev [°]HVTrafo Phase1 Temp. Avg. [°C]HVTrafo Phase2 Temp. Avg. [°C]HVTrafo Phase3 Temp. Avg. [°C]HVTrafo AirOutlet Temp. Avg. [°C]HourCounters Average Total Avg. [h]HourCounters Average GridOn Avg. [h]HourCounters Average GridOk Avg. [h]HourCounters Average TurbineOk Avg. [h]HourCounters Average Run Avg. [h]HourCounters Average Gen1 Avg. [h]HourCounters Average Gen2 Avg. [h]HourCounters Average Yaw Avg. [h]HourCounters Average ServiceOn Avg. [h]HourCounters Average AmbientOk Avg. [h]HourCounters Average WindOk Avg. [h]HourCounters Average AlarmActive Avg. [h]Total hour counter [h]Grid on hours [h]Grid ok hours [h]Turbine ok hours [h]Run hours [h]Generator 1 hours [h]Generator 2 hours [h]Yaw hours [h]Service hours [h]Ambient ok hours [h]Wind ok hours [h]Production LatestAverage Active Power Gen 0 Avg. [W]Production LatestAverage Active Power Gen 1 Avg. [W]Production LatestAverage Active Power Gen 2 Avg. [W]Production LatestAverage Total Active Power Avg. [W]Production LatestAverage Reactive Power Gen 0 Avg. [var]Production LatestAverage Reactive Power Gen 1 Avg. [var]Production LatestAverage Reactive Power Gen 2 Avg. [var]Production LatestAverage Total Reactive Power Avg. [var]Active power generator 0, Total accumulated [W]Active power generator 1, Total accumulated [W]Active power generator 2, Total accumulated [W]Total Active power [W]Reactive power generator 0,Total accumulated [var]Reactive power generator 1, Total accumulated [var]Reactive power generator 2, Total accumulated [var]Total reactive power [var]
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